# llm_cache

draft_name: draft-yu-ai-agent-use-cases-in-6g
prompt_hash: df1a10e943a6e7dc
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:25:50.356985+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-yu-ai-agent-use-cases-in-6g | AI Agent Use Cases and Requirements in 6G Network | 15pg
  Abstract: This draft introduces use cases related to AI Agents in 6G networks,
     primarily referencing the technical report of 3GPP SA1 R20 Study on
     6G Use Cases and Service Requirements (TR 22.870).  It also
     elaborates on some of the requirements for introducing AI Agents into
     6G networks from the perspective of operators.





  Network Working Group                                              M. Yu
  Internet-Draft                                                   A. Wang
  Intended status: Informational                                     J. Li
  Expires: 9 July 2026                                               Z. Li
                                                             China Telecom
                                                            5 January 2026


             AI Agent Use Cases and Requirements in 6G Network
                    draft-yu-ai-agent-use-cases-in-6g-02

  Abstract

     This draft introduces use cases related to AI Agents in 6G networks,
     primarily referencing the technical report of 3GPP SA1 R20 Study on
     6G Use Cases and Service Requirements (TR 22.870).  It also
     elaborates on some of the requirements for introducing AI Agents into
     6G networks from the perspective of operators.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 9 July 2026.

  Copyright Notice

     Copyright (c) 2026 IETF Trust and the persons identified as the
     document authors.  All rights reserved.











  Yu, et al.                 Expires 9 July 2026                  [Page 1]


  Internet-Draft  AI Agent Use Cases and Requirements in 6    January 2026


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
     2.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . .   4
       2.1.  Intent-based 6G Services Enabled by Network AI Agents . .   4
         2.1.1.  Use Case On 6G Network Providing On-demand Networking
                 with AI Agent . . . . . . . . . . . . . . . . . . . .   4
         2.1.2.  Use Case On Intelligent Calling Services  . . . . . .   5
         2.1.3.  Use Case On Disaster Rescue Planning Enabled By Network
             

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Intent-based 6G Services with Network AI Agents",
      "description": "AI agents embedded in 6G networks that can interpret user intents and automatically configure network services accordingly. These agents translate high-level user requirements into specific network configurations and service provisioning.",
      "type": "mechanism"
    },
    {
      "title": "On-demand Networking with AI Agent",
      "description": "A system where AI agents dynamically provision and configure network resources based on real-time demand patterns. The agents can automatically scale network capacity and adjust routing to meet changing service requirements.",
      "type": "pattern"
    },
    {
      "title": "Intelligent Calling Services",
      "description": "AI-enhanced voice and communication services that can understand context, preferences, and optimize call routing and quality. These services leverage AI agents to provide personalized communication experiences.",
      "type": "extension"
    },
    {
      "title": "Disaster Rescue Planning Network AI Agent",
      "description": "Specialized AI agents that can rapidly reconfigure network infrastructure and services during emergency situations. They coordinate rescue operations by optimizing communication channels and resource allocation.",
      "type": "mechanism"
    },
    {
      "title": "6G Network AI Agent Requirements Framework",
      "description": "A comprehensive set of technical and operational requirements for deploying AI agents in 6G networks from an operator perspective. This includes performance, security, and interoperability specifications.",
      "type": "requirement"
    }
  ]


draft_name: draft-yu-dmsc-ai-agent-use-cases-in-6g
prompt_hash: 0a1b6c159e3d8fa0
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:25:58.241663+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-yu-dmsc-ai-agent-use-cases-in-6g | AI Agent Use Cases and Requirements in 6G Network | 10pg
  Abstract: This draft introduces use cases related to AI Agents in 6G networks,
     primarily referencing the technical report of 3GPP SA1 R20 Study on
     6G Use Cases and Service Requirements (TR 22.870).  It also
     elaborates on some of the requirements for introducing AI Agents into
     6G networks from the perspective of operators.





  Network Working Group                                              M. Yu
  Internet-Draft                                                   A. Wang
  Intended status: Informational                                     J. Li
  Expires: 16 July 2026                                              Z. Li
                                                             China Telecom
                                                           12 January 2026


             AI Agent Use Cases and Requirements in 6G Network
                 draft-yu-dmsc-ai-agent-use-cases-in-6g-01

  Abstract

     This draft introduces use cases related to AI Agents in 6G networks,
     primarily referencing the technical report of 3GPP SA1 R20 Study on
     6G Use Cases and Service Requirements (TR 22.870).  It also
     elaborates on some of the requirements for introducing AI Agents into
     6G networks from the perspective of operators.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 16 July 2026.

  Copyright Notice

     Copyright (c) 2026 IETF Trust and the persons identified as the
     document authors.  All rights reserved.











  Yu, et al.                Expires 16 July 2026                  [Page 1]


  Internet-Draft  AI Agent Use Cases and Requirements in 6    January 2026


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     2.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . .   3
       2.1.  Intent-based 6G Services Enabled by Network AI Agents . .   4
       2.2.  Device-Network Collaboration  . . . . . . . . . . . . . .   5
       2.3.  Multiple Devices Collaboration  . . . . . . . . . . . . .   5
       2.4.  Network-Application Collaboration . . . . . . . . . . . .   6
     3.  Potential Requirements for 6G Network . . . . . . . . . . . .   7
    

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Intent-based 6G Service Provisioning",
      "description": "Network AI agents interpret user intent expressed in natural language to automatically configure and provision 6G network services. The system translates high-level user requirements into specific network configurations without manual intervention.",
      "type": "mechanism"
    },
    {
      "title": "Device-Network AI Agent Collaboration",
      "description": "Coordinated interaction between AI agents running on user devices and network-side AI agents to optimize service delivery. This enables distributed intelligence across the device-network boundary for enhanced performance.",
      "type": "architecture"
    },
    {
      "title": "Multi-Device AI Agent Coordination",
      "description": "AI agents deployed across multiple user devices collaborate to achieve common objectives or shared tasks. This pattern enables coordinated behavior and resource sharing among distributed devices in 6G networks.",
      "type": "pattern"
    },
    {
      "title": "Network-Application AI Agent Interface",
      "description": "Standardized collaboration mechanism between network-resident AI agents and application-layer AI agents. This enables applications to leverage network intelligence while allowing the network to optimize based on application requirements.",
      "type": "protocol"
    },
    {
      "title": "AI Agent Service Requirements Framework",
      "description": "Technical requirements specification for integrating AI agents into 6G network infrastructure from operator perspective. Defines performance, security, and operational constraints for AI agent deployment.",
      "type": "requirement"
    }
  ]


draft_name: draft-yuan-rtgwg-security-agent-usecase
prompt_hash: 00edeb28b9095c31
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:26:06.742751+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-yuan-rtgwg-security-agent-usecase | Use cases of the AI Network Security Agent | 7pg
  Abstract: Core network devices like routers fulfill dual roles of data
     forwarding and security protection.  However, escalating threats
     (e.g., zero-day vulnerabilities, DDoS attacks) expose limitations of
     traditional security—relying on static ACLs, signature-based
     detection, and manual configuration—causing delayed responses, high
     false positives, and protection gaps.  This paper proposes AI Network
     Security Agents: intelligent software components leveraging machine
     learning, behavioral analysis, and real-time data fusion, with three
     core capabilities (adaptive learning, automation, distributed
     collaboration) to shift security from passive to intelligent.  Four
     key scenarios are outlined: dynamic defense against unknown threats
     via baselines and tracing; ACL optimization via intent parsing;
     configuration security via baseline checks and simulation; and
     collaborative defense via intelligence aggregation and linked
     responses.  AI Agents turn routers into active security
     orchestrators, enhancing threat protection and operational
     efficiency.





  Network Working Group                                            Q. Yuan
  Internet-Draft                                                    J. Mao
  Intended status: Standards Track                                  B. Liu
  Expires: 5 May 2026                                              N. Geng
                                                                  X. Shang
                                                                    Q. Gao
                                                                     Z. Li
                                                       Huawei Technologies
                                                           1 November 2025


                 Use cases of the AI Network Security Agent
                 draft-yuan-rtgwg-security-agent-usecase-00

  Abstract

     Core network devices like routers fulfill dual roles of data
     forwarding and security protection.  However, escalating threats
     (e.g., zero-day vulnerabilities, DDoS attacks) expose limitations of
     traditional security—relying on static ACLs, signature-based
     detection, and manual configuration—causing delayed responses, high
     false positives, and protection gaps.  This paper proposes AI Network
     Security Agents: intelligent software components leveraging machine
     learning, behavioral analysis, and real-time data fusion, with three
     core capabilities (adaptive learning, automation, distributed
     collaboration) to shift security from passive to intelligent.  Four
     key scenarios are outlined: dynamic defense against unknown threats
     via baselines and tracing; ACL optimization via intent parsing;
     configuration security via baseline checks and simulation; and
     collaborative defense via intelligence aggregation and linked
     responses.  AI Agents turn routers into active security
     orchestrators, enhancing threat protection and operational
     efficiency.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."



  Yuan, et al.               Expires 5 May 2026                   [Page 1]


  Internet-Draft           Security Agent Usecase            November 2025


     This Internet-Draft will expire on 5 May 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https:/

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "AI Network Security Agent",
      "description": "Intelligent software components deployed on network devices that leverage machine learning, behavioral analysis, and real-time data fusion. These agents provide adaptive learning, automation, and distributed collaboration capabilities to transform passive security into intelligent active protection.",
      "type": "architecture"
    },
    {
      "title": "Dynamic Baseline-Based Threat Detection",
      "description": "Mechanism that establishes behavioral baselines for network traffic and uses deviation detection with tracing capabilities to identify unknown threats. Replaces static signature-based detection with adaptive learning approaches.",
      "type": "mechanism"
    },
    {
      "title": "AI-Driven ACL Optimization",
      "description": "System that parses security intent and automatically optimizes Access Control Lists using machine learning. Reduces manual configuration overhead and improves rule effectiveness through intelligent analysis.",
      "type": "mechanism"
    },
    {
      "title": "Configuration Security Validation",
      "description": "Framework that performs baseline checks and simulation of network configurations before deployment. Prevents misconfigurations and security gaps through automated validation processes.",
      "type": "mechanism"
    },
    {
      "title": "Collaborative Threat Intelligence",
      "description": "Distributed system where security agents aggregate threat intelligence across multiple network devices and coordinate linked defensive responses. Enables network-wide security orchestration through agent cooperation.",
      "type": "pattern"
    },
    {
      "title": "Real-Time Data Fusion Engine",
      "description": "Component that combines multiple data sources in real-time to provide comprehensive situational awareness for security decisions. Integrates traffic patterns, device telemetry, and threat indicators for enhanced detection accuracy.",
      "type": "mechanism"
    }
  ]


draft_name: draft-yuan-rtgwg-traffic-agent-usecase
prompt_hash: a5145306859a2ca4
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:26:13.303665+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-yuan-rtgwg-traffic-agent-usecase | Use cases of the AI Network Traffic Optimization Agent | 10pg
  Abstract: This document introduces AI Network Traffic Optimization Agents as a
     dynamic alternative to traditional static network optimization
     methods.  These AI entities analyze real-time network status (e.g.,
     latency, node load) and adjust resources flexibly—deployed centrally
     or on devices—to enhance efficiency, ensure service quality, and cut
     operational costs.  It defines network traffic optimization
     (maximizing resource use, meeting QoS) and AI agents (autonomous,
     learning entities that reduce manual work), then details three key
     application scenarios: tunnel adjustment (adaptive routing,
     predictive bandwidth, fault recovery), traffic steering
     (classification, application-aware policies, pre-emptive load
     balancing), and network slice adjustment (lifecycle automation, SLA
     compliance, slice-specific fault fixes).  The document emphasizes the
     agents’ role in enabling SLA-compliant, autonomous optimization for
     complex networks.





  Network Working Group                                            Q. Yuan
  Internet-Draft                                                    J. Mao
  Intended status: Standards Track                                  B. Liu
  Expires: 5 May 2026                                              N. Geng
                                                                  X. Shang
                                                                    Q. Gao
                                                                     Z. Li
                                                       Huawei Technologies
                                                           1 November 2025


           Use cases of the AI Network Traffic Optimization Agent
                 draft-yuan-rtgwg-traffic-agent-usecase-00

  Abstract

     This document introduces AI Network Traffic Optimization Agents as a
     dynamic alternative to traditional static network optimization
     methods.  These AI entities analyze real-time network status (e.g.,
     latency, node load) and adjust resources flexibly—deployed centrally
     or on devices—to enhance efficiency, ensure service quality, and cut
     operational costs.  It defines network traffic optimization
     (maximizing resource use, meeting QoS) and AI agents (autonomous,
     learning entities that reduce manual work), then details three key
     application scenarios: tunnel adjustment (adaptive routing,
     predictive bandwidth, fault recovery), traffic steering
     (classification, application-aware policies, pre-emptive load
     balancing), and network slice adjustment (lifecycle automation, SLA
     compliance, slice-specific fault fixes).  The document emphasizes the
     agents’ role in enabling SLA-compliant, autonomous optimization for
     complex networks.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 5 May 2026.



  Yuan, et al.               Expires 5 May 2026                   [Page 1]


  Internet-Draft            Traffic Agent Usecase            November 2025


  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "AI Network Traffic Optimization Agent",
      "description": "Autonomous AI entities that analyze real-time network status (latency, node load) and dynamically adjust network resources. These agents can be deployed centrally or distributed on network devices to replace static optimization methods.",
      "type": "architecture"
    },
    {
      "title": "Adaptive Tunnel Adjustment",
      "description": "AI-driven mechanism for dynamic routing path optimization, predictive bandwidth allocation, and automated fault recovery in network tunnels. Enables real-time adaptation based on network conditions.",
      "type": "mechanism"
    },
    {
      "title": "AI-Based Traffic Steering",
      "description": "Intelligent traffic classification and application-aware policy enforcement with pre-emptive load balancing capabilities. Uses AI to optimize traffic flow distribution across network paths.",
      "type": "mechanism"
    },
    {
      "title": "Autonomous Network Slice Management",
      "description": "AI agent-controlled network slice lifecycle automation including SLA compliance monitoring and slice-specific fault remediation. Provides automated management of network slicing resources.",
      "type": "mechanism"
    },
    {
      "title": "Real-time Network Status Analysis",
      "description": "Continuous monitoring and analysis of network metrics such as latency, node load, and resource utilization. Forms the data foundation for AI-driven optimization decisions.",
      "type": "pattern"
    }
  ]


draft_name: draft-yue-anima-agent-recovery-networks
prompt_hash: ea18d9c1dcc39c57
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:26:21.381544+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-yue-anima-agent-recovery-networks | Task-Oriented Multi-Agent Recovery Framework for High-Reliability in Converged Mobile Networks | 11pg
  Abstract: This document defines a task-oriented, agent-based method for fault
     recovery in converged public-private mobile networks.  The proposed
     method introduces a multi-agent collaboration framework that enables
     autonomous failure detection, scoped diagnosis, inter-domain
     coordination, and intent-driven policy reconfiguration.  It is
     particularly applicable in complex 5G/6G network deployments, such as
     Multi-Operator Core Networks (MOCN) and Standalone Non-Public
     Networks (SNPN), where traditional centralized management is
     insufficient for ensuring high service reliability and dynamic
     recovery.  The document also specifies protocol requirements for
     inter-agent communication, state consistency, and secure
     coordination, aiming to support interoperability and resilience
     across heterogeneous network domains.





  anima                                                        Y. Yue, Ed.
  Internet-Draft                                             X. Zhang, Ed.
  Intended status: Standards Track                            China Unicom
  Expires: 5 February 2026                                   4 August 2025


    Task-Oriented Multi-Agent Recovery Framework for High-Reliability in
                         Converged Mobile Networks
                 draft-yue-anima-agent-recovery-networks-00

  Abstract

     This document defines a task-oriented, agent-based method for fault
     recovery in converged public-private mobile networks.  The proposed
     method introduces a multi-agent collaboration framework that enables
     autonomous failure detection, scoped diagnosis, inter-domain
     coordination, and intent-driven policy reconfiguration.  It is
     particularly applicable in complex 5G/6G network deployments, such as
     Multi-Operator Core Networks (MOCN) and Standalone Non-Public
     Networks (SNPN), where traditional centralized management is
     insufficient for ensuring high service reliability and dynamic
     recovery.  The document also specifies protocol requirements for
     inter-agent communication, state consistency, and secure
     coordination, aiming to support interoperability and resilience
     across heterogeneous network domains.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 5 February 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.




  Yue & Zhang              Expires 5 February 2026                [Page 1]


  Internet-Draft  Task-Oriented Multi-Agent Recovery Frame     August 2025


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
     2.  Conv

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Task-Oriented Multi-Agent Recovery Framework",
      "description": "A collaborative framework where multiple agents work together to perform autonomous failure detection, scoped diagnosis, and recovery coordination. Each agent is assigned specific tasks within the overall recovery process.",
      "type": "architecture"
    },
    {
      "title": "Inter-Domain Coordination Mechanism",
      "description": "A coordination system that enables agents to work across different network domains, particularly for MOCN and SNPN deployments. Supports heterogeneous network domain interoperability.",
      "type": "mechanism"
    },
    {
      "title": "Intent-Driven Policy Reconfiguration",
      "description": "A policy management approach that uses high-level intent specifications to drive automatic network reconfiguration during fault recovery. Translates recovery objectives into actionable configuration changes.",
      "type": "mechanism"
    },
    {
      "title": "Inter-Agent Communication Protocol Requirements",
      "description": "Protocol specifications defining how agents communicate with each other during recovery operations. Includes requirements for message formats, coordination semantics, and interaction patterns.",
      "type": "protocol"
    },
    {
      "title": "Scoped Diagnosis System",
      "description": "A fault diagnosis mechanism that limits the scope of analysis to relevant network segments or domains. Enables focused troubleshooting rather than network-wide analysis.",
      "type": "mechanism"
    },
    {
      "title": "State Consistency Management",
      "description": "A system for maintaining consistent state information across multiple agents during recovery operations. Ensures all agents have coherent view of network status and recovery progress.",
      "type": "mechanism"
    }
  ]


draft_name: draft-yue-moq-transporting-sensing-data
prompt_hash: cb0eed92e1a5c6fd
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:26:28.215734+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-yue-moq-transporting-sensing-data | Challenges in Transporting Sensing Data with Media Over QUIC | 18pg
  Abstract: This document proposes leveraging Media Over QUIC (MOQ) to address
     the challenges of transmitting large-scale, real-time sensing data in
     6G networks.  By building on QUIC's low-latency and multiplexing
     capabilities, MOQ offers a flexible and efficient transport mechanism
     tailored to the dynamic and high-throughput requirements of 6G
     environments.  The approach focuses on enabling protocol adaptability
     across diverse application scenarios such as autonomous driving,
     smart cities, and industrial IoT, while ensuring efficient data
     fragmentation, secure and anonymous transmission, and end-to-end QoS
     awareness.  Through information-aware endpoints and optimized data
     delivery mechanisms, this solution supports scalable, reliable, and
     intelligent sensing data distribution in next-generation wireless
     networks.  It is also available to other types of 6G System Data
     [3GPP.22.870] besides sensing data, e.g., AI data, positioning data.





  moq                                                          Y. Yue, Ed.
  Internet-Draft                                                F. Li, Ed.
  Intended status: Standards Track                             W. Liu, Ed.
  Expires: 22 April 2026                                      China Unicom
                                                              C. Yang, Ed.
                                                          A. Akhavain, Ed.
                                                             K. Zhang, Ed.
                                             Huawei Technologies Co., Ltd.
                                                            M. Jadoon, Ed.
                                                         S. Robitzsch, Ed.
                                                  InterDigital Europe Ltd.
                                                           19 October 2025


        Challenges in Transporting Sensing Data with Media Over QUIC
                 draft-yue-moq-transporting-sensing-data-03

  Abstract

     This document proposes leveraging Media Over QUIC (MOQ) to address
     the challenges of transmitting large-scale, real-time sensing data in
     6G networks.  By building on QUIC's low-latency and multiplexing
     capabilities, MOQ offers a flexible and efficient transport mechanism
     tailored to the dynamic and high-throughput requirements of 6G
     environments.  The approach focuses on enabling protocol adaptability
     across diverse application scenarios such as autonomous driving,
     smart cities, and industrial IoT, while ensuring efficient data
     fragmentation, secure and anonymous transmission, and end-to-end QoS
     awareness.  Through information-aware endpoints and optimized data
     delivery mechanisms, this solution supports scalable, reliable, and
     intelligent sensing data distribution in next-generation wireless
     networks.  It is also available to other types of 6G System Data
     [3GPP.22.870] besides sensing data, e.g., AI data, positioning data.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."



  Yue, et al.               Expires 22 April 2026                 [Page 1]


  Internet-Draft   Challenges in Transporting Sensing Data    October 2025


     This Internet-Draft will expire on 22 April 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.


  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "MOQ-based Sensing Data Transport",
      "description": "Leverages Media Over QUIC (MOQ) protocol to transport large-scale, real-time sensing data in 6G networks. Builds on QUIC's low-latency and multiplexing capabilities for high-throughput requirements.",
      "type": "protocol"
    },
    {
      "title": "Information-aware Endpoints",
      "description": "Endpoints that are aware of the type and characteristics of sensing data being transmitted. Enables optimized data delivery mechanisms based on data properties.",
      "type": "architecture"
    },
    {
      "title": "Sensing Data Fragmentation",
      "description": "Efficient mechanism for fragmenting large sensing data payloads for transmission over MOQ. Addresses the challenge of handling variable-size sensing data in real-time scenarios.",
      "type": "mechanism"
    },
    {
      "title": "End-to-end QoS Awareness",
      "description": "Quality of Service awareness integrated into the MOQ transport for sensing data. Ensures appropriate service levels for different types of sensing applications like autonomous driving and industrial IoT.",
      "type": "requirement"
    },
    {
      "title": "6G System Data Extension",
      "description": "Extension of the sensing data transport approach to handle other types of 6G system data including AI data and positioning data. Provides unified transport mechanism for diverse 6G data types.",
      "type": "extension"
    }
  ]


draft_name: draft-yusef-lamps-rfc7030-renewal-recommendation
prompt_hash: b9fcad6b11a85e05
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:26:35.721124+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-yusef-lamps-rfc7030-renewal-recommendation | Certificate Renewal Recommendations for Enrollment over Secure Transport | 7pg
  Abstract: This document describes an extension to RFC7030, Enrollment over
     Secure Transport to give an indication to a end-entity device when it
     should start attempting to renew its certificates.

     Prior art is that client decides, with a typical recommmendation to
     start when the remaining lifetime of the certificate is at the 50%
     point.  As typical certificate lifetimes are reduced from years to
     fractions of a year, the 50% may be far too early, and this document
     provides a way to give alternate advice.





  LAMPS Working Group                                       R. Shekh-Yusef
  Internet-Draft                                                     Ciena
  Intended status: Standards Track                           M. Richardson
  Expires: 6 April 2026                           Sandelman Software Works
                                                              M. Ounsworth
                                                           Entrust Limited
                                                            3 October 2025


  Certificate Renewal Recommendations for Enrollment over Secure Transport
            draft-yusef-lamps-rfc7030-renewal-recommendation-03

  Abstract

     This document describes an extension to RFC7030, Enrollment over
     Secure Transport to give an indication to a end-entity device when it
     should start attempting to renew its certificates.

     Prior art is that client decides, with a typical recommmendation to
     start when the remaining lifetime of the certificate is at the 50%
     point.  As typical certificate lifetimes are reduced from years to
     fractions of a year, the 50% may be far too early, and this document
     provides a way to give alternate advice.

  About This Document

     This note is to be removed before publishing as an RFC.

     Status information for this document may be found at
     https://datatracker.ietf.org/doc/draft-yusef-lamps-rfc7030-renewal-
     recommendation/.

     Discussion of this document takes place on the lamps Working Group
     mailing list (mailto:spasm@ietf.org), which is archived at
     https://mailarchive.ietf.org/arch/browse/spasm/.  Subscribe at
     https://www.ietf.org/mailman/listinfo/spasm/.

     Source for this draft and an issue tracker can be found at
     https://github.com/mcr/rfc7030-renewal-recommendation.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.







  Shekh-Yusef, et al.       Expires 6 April 2026                  [Page 1]


  Internet-Draft                  est-renew                   October 2025


     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 6 April 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Pl

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "EST Certificate Renewal Timing Extension",
      "description": "An extension to RFC7030 Enrollment over Secure Transport that allows the CA to provide specific renewal timing recommendations to end-entity devices. Replaces the typical 50% certificate lifetime rule with CA-provided guidance.",
      "type": "extension"
    },
    {
      "title": "Dynamic Renewal Window Calculation",
      "description": "A mechanism for CAs to calculate and communicate optimal certificate renewal timing based on actual certificate lifetimes rather than fixed percentage rules. Addresses the problem where 50% renewal timing becomes impractical as certificate lifetimes decrease from years to fractions of years.",
      "type": "mechanism"
    },
    {
      "title": "CA-Directed Renewal Advisory Protocol",
      "description": "A protocol pattern where the Certificate Authority provides renewal timing advice to clients during the enrollment process. Shifts renewal decision-making from client-side heuristics to server-side policy.",
      "type": "protocol"
    },
    {
      "title": "Short-Lived Certificate Renewal Optimization",
      "description": "An architectural approach to handle renewal timing for certificates with lifetimes measured in fractions of years rather than full years. Addresses scalability and timing issues in modern PKI deployments with frequent certificate rotation.",
      "type": "architecture"
    }
  ]


draft_name: draft-zeng-mcp-troubleshooting
prompt_hash: f08bf9a1655f6cc5
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:26:43.405100+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zeng-mcp-troubleshooting | Using the Model Context Protocol (MCP) for Intent-Based Network Troubleshooting Automation | 10pg
  Abstract: The Model Context Protocol (MCP) is an open standard that enables
     Large Language Model (LLM) applications to seamlessly integrate with
     external data sources and tools by exposing Resources, Prompts and
     Tools in a JSON-RPC 2.0 transport.  This document describes a mapping
     of MCP roles, primitives and security model to the network management
     domain so that network devices act as MCP servers and network
     controllers act as MCP clients.  The goal is to provide an intent-
     based, conversational and secure approach for automated network
     troubleshooting, configuration validation, and closed-loop
     remediation without inventing new protocols or device agents.





  Network Working Group                                            G. Zeng
  Internet-Draft                                                    J. Mao
  Intended status: Informational                                    Huawei
  Expires: 23 April 2026                                   20 October 2025


      Using the Model Context Protocol (MCP) for Intent-Based Network
                         Troubleshooting Automation
                     draft-zeng-mcp-troubleshooting-00

  Abstract

     The Model Context Protocol (MCP) is an open standard that enables
     Large Language Model (LLM) applications to seamlessly integrate with
     external data sources and tools by exposing Resources, Prompts and
     Tools in a JSON-RPC 2.0 transport.  This document describes a mapping
     of MCP roles, primitives and security model to the network management
     domain so that network devices act as MCP servers and network
     controllers act as MCP clients.  The goal is to provide an intent-
     based, conversational and secure approach for automated network
     troubleshooting, configuration validation, and closed-loop
     remediation without inventing new protocols or device agents.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 23 April 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.



  Zeng & Mao                Expires 23 April 2026                 [Page 1]


  Internet-Draft              MCP for Networks                October 2025


     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   3
     3.  Architecture  . . . . . . . . . . . . . . . . . . . . . . . .   3
       3.1.  Role Allocation . . . . .

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "MCP Role Mapping for Networks",
      "description": "Maps Model Context Protocol roles to network management domain where network devices act as MCP servers and network controllers act as MCP clients. This enables LLM integration with network infrastructure using existing MCP primitives.",
      "type": "architecture"
    },
    {
      "title": "JSON-RPC 2.0 Transport for Network Management",
      "description": "Leverages JSON-RPC 2.0 transport layer from MCP to expose network Resources, Prompts and Tools. Provides standardized communication between network devices and controllers without new protocols.",
      "type": "protocol"
    },
    {
      "title": "Intent-Based Network Troubleshooting",
      "description": "Enables conversational, intent-based approach for automated network troubleshooting using LLM applications. Supports configuration validation and closed-loop remediation through MCP integration.",
      "type": "mechanism"
    },
    {
      "title": "MCP Security Model for Network Domain",
      "description": "Adapts MCP's security model to network management requirements. Provides secure access control for network device interactions through MCP server-client architecture.",
      "type": "extension"
    },
    {
      "title": "Network Device MCP Server Implementation",
      "description": "Defines how network devices implement MCP server functionality to expose their capabilities as Resources, Prompts and Tools. Enables direct LLM integration without additional device agents.",
      "type": "mechanism"
    }
  ]


draft_name: draft-zeng-nmrg-mcp-usecases-requirements
prompt_hash: f98d5592a542bd43
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:26:49.271454+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zeng-nmrg-mcp-usecases-requirements | MCP for Network Management: Problem Statement, Use Cases, and Requirements | 6pg
  Abstract: The emergence of large language models (LLMs) and AI agents is
     reshaping how network operators interact with infrastructure.
     However, current network management systems lack a standardized,
     secure, and intent-driven interface that enables AI agents to
     discover, invoke, and reason over network capabilities.  This
     document presents a problem statement for integrating the Model
     Context Protocol (MCP) into network management, outlines key use
     cases—including troubleshooting, measurement, security, and
     optimization—and specifies functional, security, and interoperability
     requirements for MCP-based network management architectures.





  Network Working Group                                            G. Zeng
  Internet-Draft                                                    Huawei
  Intended status: Informational                             February 2026
  Expires: 18 August 2026


       MCP for Network Management: Problem Statement, Use Cases, and
                                Requirements
                draft-zeng-nmrg-mcp-usecases-requirements-00

  Abstract

     The emergence of large language models (LLMs) and AI agents is
     reshaping how network operators interact with infrastructure.
     However, current network management systems lack a standardized,
     secure, and intent-driven interface that enables AI agents to
     discover, invoke, and reason over network capabilities.  This
     document presents a problem statement for integrating the Model
     Context Protocol (MCP) into network management, outlines key use
     cases—including troubleshooting, measurement, security, and
     optimization—and specifies functional, security, and interoperability
     requirements for MCP-based network management architectures.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 5 August 2026.

  Copyright Notice

     Copyright (c) 2026 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.



  Zeng                     Expires 18 August 2026                 [Page 1]


  Internet-Draft  MCP for Network Management: Problem Stat   February 2026


     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     2.  Problem Statement . . . . . . . . . . . . . . . . . . . . . .   2
     3.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . .   3
       3.1.  Troubleshooting . . . . . . . . . . . . . . . . . . . . .   3
       3.2.  Network Measurement . . .

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "MCP Network Interface",
      "description": "A standardized, secure, and intent-driven interface that enables AI agents to discover, invoke, and reason over network capabilities using the Model Context Protocol. This interface bridges AI agents with network management systems.",
      "type": "protocol"
    },
    {
      "title": "AI Agent Network Discovery",
      "description": "A mechanism allowing AI agents to automatically discover available network management capabilities and services through MCP. Enables dynamic capability enumeration for network operations.",
      "type": "mechanism"
    },
    {
      "title": "Intent-Driven Network Management",
      "description": "An approach where AI agents can express high-level network intents through MCP rather than low-level commands. The system translates intents into specific network operations.",
      "type": "pattern"
    },
    {
      "title": "MCP Network Security Model",
      "description": "Security requirements and mechanisms for protecting MCP-based interactions between AI agents and network infrastructure. Includes authentication, authorization, and secure communication protocols.",
      "type": "requirement"
    },
    {
      "title": "AI-Driven Network Troubleshooting",
      "description": "Use case where AI agents leverage MCP to perform automated network troubleshooting by accessing diagnostic tools and reasoning over network state. Enables intelligent fault isolation and resolution.",
      "type": "mechanism"
    }
  ]


draft_name: draft-zeng-opsawg-applicability-mcp-a2a
prompt_hash: 38ae9d12b0b54c54
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:26:57.447963+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zeng-opsawg-applicability-mcp-a2a | When NETCONF Is Not Enough: Applicability of MCP and A2A for Advanced Network Management Scenarios | 12pg
  Abstract: NETCONF provides robust configuration transactions and YANG-based
     data models, but falls short in scenarios requiring AI-driven
     semantic translation, long-lived cross-domain orchestration, multi-
     agent consensus, rapid DevOps iteration, or delivery of large non-
     configuration artifacts.  This document systematically analyzes the
     functional gaps and presents Model Context Protocol (MCP) and Agent-
     to-Agent (A2A) as complementary solutions.  Implementation guidance
     and coexistence models are also provided.





  Network Working Group                                            G. Zeng
  Internet-Draft                                                    J. Mao
  Intended status: Standards Track                                  B. Liu
  Expires: 6 May 2026                                              N. Geng
                                                                  X. Shang
                                                                    Q. Gao
                                                                     Z. Li
                                                                    Huawei
                                                           2 November 2025


   When NETCONF Is Not Enough: Applicability of MCP and A2A for Advanced
                        Network Management Scenarios
                 draft-zeng-opsawg-applicability-mcp-a2a-00

  Abstract

     NETCONF provides robust configuration transactions and YANG-based
     data models, but falls short in scenarios requiring AI-driven
     semantic translation, long-lived cross-domain orchestration, multi-
     agent consensus, rapid DevOps iteration, or delivery of large non-
     configuration artifacts.  This document systematically analyzes the
     functional gaps and presents Model Context Protocol (MCP) and Agent-
     to-Agent (A2A) as complementary solutions.  Implementation guidance
     and coexistence models are also provided.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 6 May 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.




  Zeng, et al.               Expires 6 May 2026                   [Page 1]


  Internet-Draft                 MCP-A2A-Gap                 November 2025


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . .

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Model Context Protocol (MCP)",
      "description": "A protocol designed to handle AI-driven semantic translation and context sharing for network management scenarios where YANG models are insufficient. Provides mechanisms for managing contextual information across network management operations.",
      "type": "protocol"
    },
    {
      "title": "Agent-to-Agent (A2A) Communication",
      "description": "A communication mechanism enabling multi-agent consensus and coordination for cross-domain network orchestration. Supports long-lived interactions between autonomous network management agents.",
      "type": "mechanism"
    },
    {
      "title": "NETCONF Gap Analysis Framework",
      "description": "A systematic analysis methodology identifying specific functional limitations of NETCONF in advanced scenarios. Categorizes gaps into AI-driven translation, cross-domain orchestration, multi-agent consensus, DevOps iteration, and large artifact delivery.",
      "type": "pattern"
    },
    {
      "title": "Large Non-Configuration Artifact Delivery",
      "description": "A mechanism for transferring substantial data objects that fall outside traditional configuration management scope. Addresses NETCONF limitations in handling large payloads beyond configuration data.",
      "type": "mechanism"
    },
    {
      "title": "Protocol Coexistence Model",
      "description": "An architectural pattern defining how MCP and A2A can operate alongside existing NETCONF deployments. Provides implementation guidance for hybrid network management environments.",
      "type": "architecture"
    }
  ]


draft_name: draft-zeng-opsawg-llm-netconf-gap
prompt_hash: 1ba3a0e8034e6b9a
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:27:05.695116+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zeng-opsawg-llm-netconf-gap | Gap Analysis of Network Configuration Protocols in LLM-Driven Intent-Based Networking | 9pg
  Abstract: Large Language Models (LLMs) are entering network operations through
     natural-language intent interfaces.  Existing south-bound protocols
     (NETCONF, RESTCONF, gNMI, MCP, A2A) were not designed for
     conversational, semantically-rich, multi-agent orchestration.  This
     document provides a systematic gap analysis and identifies extension
     points for each protocol to meet intent-based networking
     requirements.





  Network Working Group                                            G. Zeng
  Internet-Draft                                                    J. Mao
  Intended status: Informational                                    B. Liu
  Expires: 6 May 2026                                              N. Geng
                                                                  X. Shang
                                                                    Q. Gao
                                                                     Z. Li
                                                                    Huawei
                                                           2 November 2025


   Gap Analysis of Network Configuration Protocols in LLM-Driven Intent-
                              Based Networking
                    draft-zeng-opsawg-llm-netconf-gap-00

  Abstract

     Large Language Models (LLMs) are entering network operations through
     natural-language intent interfaces.  Existing south-bound protocols
     (NETCONF, RESTCONF, gNMI, MCP, A2A) were not designed for
     conversational, semantically-rich, multi-agent orchestration.  This
     document provides a systematic gap analysis and identifies extension
     points for each protocol to meet intent-based networking
     requirements.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 6 May 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.





  Zeng, et al.               Expires 6 May 2026                   [Page 1]


  Internet-Draft               LLM Netconf Gap               November 2025


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     2.  Conventions and Definitions . . . . . . . . . . . . . . . . .   3
     3.  G

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Natural Language Intent Interface Gap",
      "description": "Existing southbound protocols (NETCONF, RESTCONF, gNMI, MCP, A2A) lack native support for processing natural language intents from LLMs. Current protocols require structured data formats that don't align with conversational AI outputs.",
      "type": "requirement"
    },
    {
      "title": "Multi-Agent Orchestration Extension",
      "description": "Traditional network configuration protocols need extensions to support coordination between multiple LLM agents working simultaneously on network operations. Current single-session models are insufficient for distributed AI-driven management.",
      "type": "extension"
    },
    {
      "title": "Semantic Context Preservation Mechanism",
      "description": "Network protocols require mechanisms to maintain semantic context across multiple configuration transactions when driven by LLM conversations. Current stateless approaches lose conversational context needed for intent interpretation.",
      "type": "mechanism"
    },
    {
      "title": "Intent-to-Configuration Translation Protocol",
      "description": "A systematic protocol extension framework is needed to bridge the gap between high-level natural language intents and low-level device configurations. This would standardize how LLM outputs map to existing protocol operations.",
      "type": "protocol"
    },
    {
      "title": "Conversational State Management Pattern",
      "description": "Network management protocols need patterns to handle conversational state across multiple interactions, enabling LLMs to reference previous configurations and maintain dialogue context during network operations.",
      "type": "pattern"
    }
  ]


draft_name: draft-zhang-agent-gap-network
prompt_hash: bc8a780f77f40578
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:27:13.097247+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhang-agent-gap-network | Problem Statement and Gap Analysis for Agent-enabled Mobile Core Network | 6pg
  Abstract: This document provides the problem statement and gap analysis of
     agent-enabled mobile core network.





  Network Working Group                                      Y. Zhang, Ed.
  Internet-Draft                                             X. Zhang, Ed.
  Intended status: Standards Track                             Y. Yue, Ed.
  Expires: 8 January 2026                                     China Unicom
                                                               7 July 2025


  Problem Statement and Gap Analysis for Agent-enabled Mobile Core Network
                      draft-zhang-agent-gap-network-00

  Abstract

     This document provides the problem statement and gap analysis of
     agent-enabled mobile core network.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 8 January 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.






  Zhang, et al.            Expires 8 January 2026                 [Page 1]


  Internet-Draft  Problem and Gap for Agent-enabled Networ       July 2025


  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     2.  Conventions and Definitions . . . . . . . . . . . . . . . . .   3
     3.  Problem statement . . . . . . . . . . . . . . . . . . . . . .   3
       3.1.  Changes in Interaction Content  . . . . . . . . . . . . .   3
       3.2.  Changes in Interaction Entity . . . . . . . . . . . . . .   3
       3.3.  Changes in Interaction Protocol . . . . . . . . . . . . .   4
     4.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . .   4
       4.1.  Network for Agent Communication . . . . . . . . . . . . .   4
       4.2.  Agent-based Network Enhancement . . . . . . . . . . . . .   4
     5.  Gap Analysis  . . . . . . . . . . . . . . . . . . . . . . . .   4
       5.1.  GAP analysis of service capabilities  . . . . . . . . . .   4
   

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Agent-enabled Mobile Core Network Architecture",
      "description": "A mobile core network architecture that integrates AI agents to enhance network operations and service delivery. This represents a fundamental shift from traditional mobile core designs.",
      "type": "architecture"
    },
    {
      "title": "Network for Agent Communication",
      "description": "Network infrastructure specifically designed to support communication between AI agents in mobile core environments. Addresses the unique requirements of agent-to-agent interactions.",
      "type": "pattern"
    },
    {
      "title": "Agent-based Network Enhancement",
      "description": "Use of AI agents to improve existing network functions and capabilities in mobile core networks. Focuses on leveraging agent intelligence for network optimization.",
      "type": "mechanism"
    },
    {
      "title": "Changes in Interaction Content Requirements",
      "description": "Modified data exchange formats and content types needed when agents participate in mobile network operations. Addresses what information agents need to share.",
      "type": "requirement"
    },
    {
      "title": "Changes in Interaction Entity Framework",
      "description": "New entity models and roles when AI agents become participants in mobile core network operations. Defines how agents integrate with existing network entities.",
      "type": "architecture"
    },
    {
      "title": "Changes in Interaction Protocol",
      "description": "Protocol modifications or new protocols needed to support agent interactions in mobile core networks. Addresses how agents communicate with network components.",
      "type": "protocol"
    }
  ]


draft_name: draft-zhang-aiproto-svcb-mapping-for-agents
prompt_hash: c6ec753d0b15a0a4
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:27:20.342362+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhang-aiproto-svcb-mapping-for-agents | Service Binding Mapping for Agents | 6pg
  Abstract: With the continuous introduction of intelligent agent communication
     and interaction protocols, the current DNS cannot adequately meet the
     requirements for agent service resolution.  This document defines a
     new DNS resource record type, AGENT, which is a SVCB-compatible RR
     type, and specifies the mapping specifications.





  Network Working Group                                           M. Zhang
  Internet-Draft                                                  Z.W. Yan
  Intended status: Informational                                 K.J. Dong
  Expires: 6 July 2026                                             H.T. Li
                                                                     CNNIC
                                                            2 January 2026


                     Service Binding Mapping for Agents
               draft-zhang-aiproto-svcb-mapping-for-agents-01

  Abstract

     With the continuous introduction of intelligent agent communication
     and interaction protocols, the current DNS cannot adequately meet the
     requirements for agent service resolution.  This document defines a
     new DNS resource record type, AGENT, which is a SVCB-compatible RR
     type, and specifies the mapping specifications.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 6 July 2026.

  Copyright Notice

     Copyright (c) 2026 IETF Trust and the persons identified as the
     document authors.  All rights reserved.











  Zhang, et al.              Expires 6 July 2026                  [Page 1]


  Internet-Draft     Service Binding Mapping for Agents       January 2026


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Requirements notation . . . . . . . . . . . . . . . . . . . .   2
     2.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     3.  Basic requirements  . . . . . . . . . . . . . . . . . . . . .   3
     4.  SvcParamKeys defined by SVCB  . . . . . . . . . . . . . . . .   3
       4.1.  "alpn"  . . . . . . . . . . . . . . . . . . . . . . . . .   3
       4.2.  "port"  . . . . . . . . . . . . . . . . . . . . . . . . .   3
       4.3.  "ipv4hint" and "ipv6hint" . . . . . . . . . . . . . . . .   4


  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "AGENT DNS Resource Record",
      "description": "A new DNS resource record type called AGENT that is SVCB-compatible for intelligent agent service resolution. This extends DNS capabilities beyond traditional web services to support agent-specific discovery.",
      "type": "extension"
    },
    {
      "title": "SVCB-Compatible Agent Mapping",
      "description": "Extension of the Service Binding (SVCB) record format to support agent communication protocols. Leverages existing SVCB infrastructure while adding agent-specific service parameters.",
      "type": "mechanism"
    },
    {
      "title": "Agent-Specific ALPN Support",
      "description": "Application of Application Layer Protocol Negotiation (ALPN) parameter within AGENT records to identify agent communication protocols. Enables protocol negotiation for intelligent agent interactions.",
      "type": "mechanism"
    },
    {
      "title": "Agent Service Port Mapping",
      "description": "Port parameter specification for AGENT records to direct agent communications to specific service endpoints. Allows agents to connect to designated ports for their protocols.",
      "type": "mechanism"
    },
    {
      "title": "Agent IP Hint System",
      "description": "IPv4 and IPv6 hint parameters for AGENT records to provide connection optimization for agent services. Reduces DNS lookup overhead for agent-to-agent communications.",
      "type": "mechanism"
    }
  ]


draft_name: draft-zhang-dmsc-ioa-semantic-interaction
prompt_hash: 45cef0ede1f06e17
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:27:28.090096+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhang-dmsc-ioa-semantic-interaction | Ontology-based Semantic Interaction for Internet of Agents | 19pg
  Abstract: This document specifies a normative semantic layer for agent-to-agent
     interaction in the Internet of Agents (IoA).  The semantic layer
     provides a common ontology model and a JSON-LD serialization profile
     (RECOMMENDED), while allowing other RDF serializations for expressing
     capabilities, intents, tasks, and context.  The document defines
     required classes and properties, a negotiation procedure, and
     alignment rules for heterogeneous ontologies.  This layer is designed
     to be used by interaction and discovery protocols but does not define
     transport, session, or security protocols.  It enables deterministic
     semantic interoperability across domains.





  Network Working Group                                           L. Zhang
  Internet-Draft                                                   S. Wang
  Intended status: Standards Track                                   Y. Li
  Expires: 31 August 2026                                          H. Yang
                                        AsiaInfo Technologies (China) Inc.
                                                          27 February 2026


         Ontology-based Semantic Interaction for Internet of Agents
                draft-zhang-dmsc-ioa-semantic-interaction-01

  Abstract

     This document specifies a normative semantic layer for agent-to-agent
     interaction in the Internet of Agents (IoA).  The semantic layer
     provides a common ontology model and a JSON-LD serialization profile
     (RECOMMENDED), while allowing other RDF serializations for expressing
     capabilities, intents, tasks, and context.  The document defines
     required classes and properties, a negotiation procedure, and
     alignment rules for heterogeneous ontologies.  This layer is designed
     to be used by interaction and discovery protocols but does not define
     transport, session, or security protocols.  It enables deterministic
     semantic interoperability across domains.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 31 August 2026.

  Copyright Notice

     Copyright (c) 2026 IETF Trust and the persons identified as the
     document authors.  All rights reserved.






  Zhang, et al.            Expires 31 August 2026                 [Page 1]


  Internet-Draft        Semantic Interaction for IoA         February 2026


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
     2.  Conventions and Terminology . . . . . . . . . . . . . . . . .   3
     3.  Sco

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "IoA Common Ontology Model",
      "description": "A standardized ontology framework defining required classes and properties for expressing agent capabilities, intents, tasks, and context in Internet of Agents. Uses RDF-based semantic modeling to enable interoperability across heterogeneous agent systems.",
      "type": "architecture"
    },
    {
      "title": "JSON-LD Serialization Profile",
      "description": "A recommended JSON-LD serialization format for the IoA semantic layer, providing a web-friendly representation while maintaining RDF compatibility. Allows other RDF serializations as alternatives for expressing semantic information.",
      "type": "protocol"
    },
    {
      "title": "Semantic Negotiation Procedure",
      "description": "A defined process for agents to negotiate semantic understanding and establish common interpretation of ontological concepts during interaction. Enables dynamic semantic agreement between heterogeneous agents.",
      "type": "mechanism"
    },
    {
      "title": "Heterogeneous Ontology Alignment Rules",
      "description": "Standardized rules and procedures for aligning different ontologies used by various agents in the IoA ecosystem. Provides deterministic semantic interoperability across different domains and agent implementations.",
      "type": "mechanism"
    },
    {
      "title": "Transport-Agnostic Semantic Layer",
      "description": "A semantic interaction layer designed to work independently of transport, session, or security protocols. Provides semantic interoperability services to higher-level interaction and discovery protocols.",
      "type": "architecture"
    }
  ]


draft_name: draft-zhang-dmsc-mas-communication
prompt_hash: d8b8d65167e88e93
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:27:36.071549+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhang-dmsc-mas-communication | Security Analysis of Multi-agents Secured Communication and Limitations of Existing Protocols | 8pg
  Abstract: Multi-agents systems (MAS) increasingly cooperate through workflow,
     orchestrated, and mesh communication patterns.  While existing
     Internet protocols provide confidentiality and endpoint
     authentication, they were not designed for agent-native semantics
     such as dynamic identity, computation-bounded requests, context
     integrity, and intermediary trust.  This document analyzes security
     risks in agent communication and identifies limitations in widely
     deployed protocols (TLS, HTTP, MQTT,A2A and etc.) and developer
     framework (AutoGen and etc.).  This document intend to establish a
     common problem statement and gap analysis to inform future IETF
     standardization.





  DMSC Working Group                                              H. Zhang
  Internet-Draft                                             China Telecom
  Intended status: Standards Track                         16 January 2026
  Expires: 20 July 2026


  Security Analysis of Multi-agents Secured Communication and Limitations
                           of Existing Protocols
                   draft-zhang-dmsc-mas-communication-00

  Abstract

     Multi-agents systems (MAS) increasingly cooperate through workflow,
     orchestrated, and mesh communication patterns.  While existing
     Internet protocols provide confidentiality and endpoint
     authentication, they were not designed for agent-native semantics
     such as dynamic identity, computation-bounded requests, context
     integrity, and intermediary trust.  This document analyzes security
     risks in agent communication and identifies limitations in widely
     deployed protocols (TLS, HTTP, MQTT,A2A and etc.) and developer
     framework (AutoGen and etc.).  This document intend to establish a
     common problem statement and gap analysis to inform future IETF
     standardization.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 20 July 2026.

  Copyright Notice

     Copyright (c) 2026 IETF Trust and the persons identified as the
     document authors.  All rights reserved.






  Zhang                     Expires 20 July 2026                  [Page 1]


  Internet-Draft  Security Analysis of Multi-agents Secure    January 2026


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     2.  Conventions used in this document . . . . . . . . . . . . . .   3
     3.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   3
     4.  Core Communication Security Risks in MAS  . . . . . . . . . .   3


  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Agent-native semantics",
      "description": "Security requirements specific to multi-agent systems including dynamic identity management, computation-bounded requests, context integrity, and intermediary trust. These differ from traditional endpoint-to-endpoint security models.",
      "type": "requirement"
    },
    {
      "title": "Multi-agent communication patterns",
      "description": "Three distinct communication patterns for agent cooperation: workflow, orchestrated, and mesh communication patterns. Each pattern presents different security challenges and trust models.",
      "type": "architecture"
    },
    {
      "title": "Dynamic identity management",
      "description": "Identity mechanisms that can change dynamically during agent interactions, unlike static endpoint authentication in traditional protocols. Required for agents that may assume different roles or capabilities during execution.",
      "type": "mechanism"
    },
    {
      "title": "Computation-bounded requests",
      "description": "Security framework for requests that are limited by computational resources or time constraints. Addresses scenarios where agents have processing limitations or operate under time-sensitive conditions.",
      "type": "mechanism"
    },
    {
      "title": "Context integrity for agents",
      "description": "Mechanism to ensure that communication context and state are preserved and verified across multi-agent interactions. Goes beyond message integrity to include conversation and workflow state.",
      "type": "mechanism"
    },
    {
      "title": "Intermediary trust model",
      "description": "Trust framework for scenarios where agents communicate through intermediaries, requiring verification of intermediate nodes rather than just endpoints. Extends traditional end-to-end trust models.",
      "type": "architecture"
    }
  ]


draft_name: draft-zhang-rtgwg-ai-agents-measurement
prompt_hash: 922f3ffea536d417
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:27:41.673935+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhang-rtgwg-ai-agents-measurement | Use Cases and Requirements of Communication Protocol for Measurement Agents on Network Devices | 7pg
  Abstract: This document focuses on the use cases and requirements of
     communication protocols for measurement agents on network devices.





  rtgwg                                                           R. Zhang
  Internet-Draft                                                    J. Mao
  Intended status: Informational                                    B. Liu
  Expires: 7 May 2026                                              N. Geng
                                                                  X. Shang
                                                                    Q. Gao
                                                                     Z. Li
                                                                    Huawei
                                                           3 November 2025


    Use Cases and Requirements of Communication Protocol for Measurement
                         Agents on Network Devices
                 draft-zhang-rtgwg-ai-agents-measurement-00

  Abstract

     This document focuses on the use cases and requirements of
     communication protocols for measurement agents on network devices.

  About This Document

     This note is to be removed before publishing as an RFC.

     The latest revision of this draft can be found at
     https://example.com/LATEST.  Status information for this document may
     be found at https://datatracker.ietf.org/doc/draft-zhang-rtgwg-ai-
     agents-measurement/.

     Discussion of this document takes place on the rtgwg Working Group
     mailing list (mailto:WG@example.com), which is archived at
     https://example.com/WG.

     Source for this draft and an issue tracker can be found at
     https://github.com/USER/REPO.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.






  Zhang, et al.              Expires 7 May 2026                   [Page 1]


  Internet-Draft  Use Cases and Requirements of Communicat   November 2025


     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 7 May 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the T

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Measurement Agent Communication Protocol",
      "description": "A specialized communication protocol designed for measurement agents deployed on network devices. The protocol enables coordination and data exchange between distributed measurement agents.",
      "type": "protocol"
    },
    {
      "title": "Network Device Measurement Agents",
      "description": "Software agents deployed on network devices to perform measurement functions and coordinate with other agents. These agents require specific communication capabilities for effective operation.",
      "type": "architecture"
    },
    {
      "title": "Agent-to-Agent Coordination Pattern",
      "description": "A communication pattern that allows measurement agents to coordinate their activities across multiple network devices. This enables distributed measurement scenarios and data correlation.",
      "type": "pattern"
    },
    {
      "title": "Measurement Data Exchange Mechanism",
      "description": "A mechanism for measurement agents to exchange collected data and measurement results with each other. This supports collaborative measurement and analysis across the network.",
      "type": "mechanism"
    }
  ]


draft_name: draft-zhang-rtgwg-ai-agents-troubleshooting
prompt_hash: b1f9a6e805e0a8f4
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:27:48.014427+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhang-rtgwg-ai-agents-troubleshooting | Use Cases and Requirements of Communication Protocol for Troubleshooting Agents on Network Devices | 14pg
  Abstract: This document focuses on the use cases and requirements of
     communication protocols for troubleshooting agents on network
     devices.





  rtgwg                                                           R. Zhang
  Internet-Draft                                                    J. Mao
  Intended status: Informational                                    B. Liu
  Expires: 7 May 2026                                              N. Geng
                                                                  X. Shang
                                                                    Q. Gao
                                                                     Z. Li
                                                                    Huawei
                                                           3 November 2025


  Use Cases and Requirements of Communication Protocol for Troubleshooting
                         Agents on Network Devices
               draft-zhang-rtgwg-ai-agents-troubleshooting-00

  Abstract

     This document focuses on the use cases and requirements of
     communication protocols for troubleshooting agents on network
     devices.

  About This Document

     This note is to be removed before publishing as an RFC.

     The latest revision of this draft can be found at
     https://example.com/LATEST.  Status information for this document may
     be found at https://datatracker.ietf.org/doc/draft-zhang-rtgwg-ai-
     agents-troubleshooting/.

     Discussion of this document takes place on the rtgwg Working Group
     mailing list (mailto:WG@example.com), which is archived at
     https://example.com/WG.

     Source for this draft and an issue tracker can be found at
     https://github.com/USER/REPO.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.





  Zhang, et al.              Expires 7 May 2026                   [Page 1]


  Internet-Draft  Use Cases and Requirements of Communicat   November 2025


     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 7 May 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Sectio

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Troubleshooting Agent Communication Protocol",
      "description": "A specialized communication protocol designed for AI-based troubleshooting agents deployed on network devices. The protocol enables coordination and information exchange between distributed troubleshooting agents.",
      "type": "protocol"
    },
    {
      "title": "Network Device Agent Architecture",
      "description": "An architecture for deploying AI troubleshooting agents directly on network devices to perform autonomous fault detection and diagnosis. Agents operate locally while coordinating with other devices through specialized protocols.",
      "type": "architecture"
    },
    {
      "title": "Agent-to-Agent Coordination Mechanism",
      "description": "A mechanism enabling multiple troubleshooting agents across different network devices to share diagnostic information and coordinate troubleshooting activities. Supports distributed problem-solving across network infrastructure.",
      "type": "mechanism"
    },
    {
      "title": "Distributed Network Troubleshooting Pattern",
      "description": "A pattern where troubleshooting intelligence is distributed across network devices rather than centralized. Each device runs local agents that communicate to provide network-wide diagnostic capabilities.",
      "type": "pattern"
    }
  ]


draft_name: draft-zhang-rtgwg-llmmoe-multicast
prompt_hash: 44f5eacccaadd602
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:27:56.349037+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhang-rtgwg-llmmoe-multicast | Multicast usage in LLM MoE | 7pg
  Abstract: Large Language Models (LLMs) have been widely used in recent years.
     The Mixture of Experts (MoE) architecture is one of the features of
     LLMs that enables efficient inference and cost-effective training.
     With the MoE architecture, there are potential multicast use cases
     such as tokens dispatching.  This draft attempts to analyze these use
     cases.





  RTGWG                                                           Z. Zhang
  Internet-Draft                                                   W. Duan
  Intended status: Informational                           ZTE Corporation
  Expires: 23 April 2026                                             X. Xu
                                                              China Mobile
                                                           20 October 2025


                         Multicast usage in LLM MoE
                   draft-zhang-rtgwg-llmmoe-multicast-01

  Abstract

     Large Language Models (LLMs) have been widely used in recent years.
     The Mixture of Experts (MoE) architecture is one of the features of
     LLMs that enables efficient inference and cost-effective training.
     With the MoE architecture, there are potential multicast use cases
     such as tokens dispatching.  This draft attempts to analyze these use
     cases.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 23 April 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.










  Zhang, et al.             Expires 23 April 2026                 [Page 1]


  Internet-Draft              Abbreviated Title               October 2025


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
       1.1.  Requirements Language . . . . . . . . . . . . . . . . . .   3
     2.  Use case - tokens dispatching . . . . . . . . . . . . . . . .   3
       2.1.  Intra-node multicast  . . . . . . . . . . . . . . . . . .   4
       2.2.  Inter-node multicast  . . . . . . . . . . . . . . . . . .   4
       2.3.  Dynamic Requirements  . . . . . . . . . . . . . . . . . .   5
       2.4.  Reliability requirements  . . . . . . . .

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Token Dispatching Multicast",
      "description": "Multicast mechanism for distributing tokens from gating network to selected expert nodes in MoE architecture. Enables efficient routing of input tokens to appropriate expert models based on routing decisions.",
      "type": "mechanism"
    },
    {
      "title": "Intra-node Expert Multicast", 
      "description": "Multicast pattern for distributing tokens to multiple experts residing within the same physical node or server. Optimizes local communication between gating function and co-located expert models.",
      "type": "pattern"
    },
    {
      "title": "Inter-node Expert Multicast",
      "description": "Network-level multicast mechanism for sending tokens from gating nodes to expert nodes distributed across different physical servers. Requires network infrastructure support for efficient cross-node communication.",
      "type": "mechanism"
    },
    {
      "title": "Dynamic Multicast Group Management",
      "description": "Requirement for dynamically adjusting multicast group membership based on real-time expert selection decisions. Group composition changes per inference request based on gating network outputs.",
      "type": "requirement"
    },
    {
      "title": "MoE Reliability Requirements",
      "description": "Reliability constraints for multicast delivery in LLM inference pipelines where token loss can impact model accuracy. Defines fault tolerance needs for expert communication patterns.",
      "type": "requirement"
    }
  ]


draft_name: draft-zhang-rvp-problem-statement
prompt_hash: 0e4a88505f5d1633
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:28:04.959789+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhang-rvp-problem-statement | Problem Statements and Requirements of Real-Virtual Agent Protocol (RVP): Communication Protocol for Embodied Intelligence in Physical- Digital Continuum | 23pg
  Abstract: The Real-Virtual Agent Protocol (RVP) enables seamless coordination
    between physical entities (robots, IoT devices, manufacturing
    systems and agents) and digital agents (AI systems, software agents,
    virtual twins) through unified composite identity management,
    physical/social/production relations graph-based coordination, and
    physical constraint integration. Unlike existing protocols that
    assume peer-to-peer digital relationships (A2A for agents, MCP for
    AI tools, ANP for agent networks), RVP unifies physical and digital
    agents communication and achieves physical data loop for online
    learning for embodied agents considering both hierarchical
    physical/social/production relations and physical world constraints.
    RVP is designed for immediate deployment in modern manufacturing,
    smart cities, autonomous mobility systems, and human-AI
    collaborative environments where non-peer, partially centralized
    relations and coordination is essential for real-world embodied
    intelligence networks.

  Workgroup:Network Working Group                                     X.Zhang
  Internet-Draft:                                                    Hicagent
  draft-zhang-rvp-problem-statement-00                                Y.Zhang
  Published:20 October 2025                                           C.Zhang
  Intended status: Informational                                      M.Zhang
  Expires:20 April 2026                                         China Telecom
                                                                         W.Lu
                                                                       SUPCON




      Problem Statements and Requirements of Real-Virtual Agent Protocol
     (RVP): Communication Protocol for Embodied Intelligence in Physical-
                              Digital Continuum





      Status of this Memo

    This Internet-Draft is submitted in full conformance with the
    provisions of BCP 78 and BCP 79. This document may not be modified,
    and derivative works of it may not be created, except to publish it
    as an RFC and to translate it into languages other than English.

    This document may contain material from IETF Documents or IETF
    Contributions published or made publicly available before November
    10, 2008. The person(s) controlling the copyright in some of this
    material may not have granted the IETF Trust the right to allow
    modifications of such material outside the IETF Standards Process.
    Without obtaining an adequate license from the person(s) controlling
    the copyright in such materials, this document may not be modified
    outside the IETF Standards Process, and derivative works of it may
    not be created outside the IETF Standards Process, except to format
    it for publication as an RFC or to translate it into languages other
    than English.

    Internet-Drafts are working documents of the Internet Engineering
    Task Force (IETF), its areas, and its working groups.  Note that
    other groups may also distribute working documents as Internet-
    Drafts.

    Internet-Drafts are draft documents valid for a maximum of six
    months and may be updated, replaced, or obsoleted by other documents
    at any time.  It is inappropriate to use Internet-Drafts as reference
    material or to cite them other than as "work in progress."



      Zhang                  Expires 20,April,2026                 [Page 1]


      Internet-Draft          RVP Problem Statement             October 2025


    The list of current Internet-Drafts can be accessed at
    http://www.ietf.org/ietf/1id-abstracts.txt

    The list of Internet-Draft Shadow Directories can be accessed at
    http://www.ietf.org/shadow.html

    This Internet-Draft will expire on April 20, 2026.

      Copyright Notice

    Copyright (c) 2025 IETF Trust and the persons identified as the
    document authors. All rights reserved.

    This document is subject to BCP 78 and the IETF Trust's Legal
    Provisions Relating to IETF Doc

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Unified Composite Identity Management",
      "description": "Identity management system that bridges physical entities (robots, IoT devices) and digital agents (AI systems, virtual twins) under a single identity framework. Enables seamless coordination between physical and digital domains.",
      "type": "mechanism"
    },
    {
      "title": "Physical/Social/Production Relations Graph",
      "description": "Graph-based coordination system that models hierarchical relationships between agents considering physical constraints, social interactions, and production workflows. Supports non-peer, partially centralized coordination patterns.",
      "type": "architecture"
    },
    {
      "title": "Physical Constraint Integration",
      "description": "Integration mechanism that incorporates real-world physical limitations and constraints into digital agent communication and decision-making processes. Ensures digital agents respect physical world boundaries.",
      "type": "mechanism"
    },
    {
      "title": "Physical Data Loop for Online Learning",
      "description": "Continuous feedback mechanism that enables embodied agents to learn from real-world physical interactions and update their behavior in real-time. Creates closed-loop learning between physical actions and digital intelligence.",
      "type": "pattern"
    },
    {
      "title": "Physical-Digital Continuum Protocol",
      "description": "Communication protocol architecture that unifies physical and digital agent interactions, moving beyond peer-to-peer assumptions of existing protocols (A2A, MCP, ANP). Designed for embodied intelligence networks with hierarchical relations.",
      "type": "protocol"
    }
  ]


draft_name: draft-zhao-ccamp-actn-optical-network-agent
prompt_hash: 0778891fb3f99e0d
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:28:11.378388+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhao-ccamp-actn-optical-network-agent | Integration of Network Management Agent (NMA) into ACTN-Based Optical Network | 10pg
  Abstract: With the growth of optical network scale, the complexity of network
     operation and maintenance has increased dramatically.  Enhancing the
     intelligence level of optical network operation and management and
     building high-level autonomous optical networks have become the
     common vision of global operators.  The development of AI, especially
     large AI model technologies, provides a feasible technical path for
     realizing autonomous perception, decision-making, analysis, and
     execution.  The existing ACTN architecture provides network
     abstraction and control functions for optical networks but lacks
     higher-level autonomous capabilities.

     This document explores the introduction of AI based Network
     Management Agent(NMA) functions into ACTN-based optical networks to
     achieve high-level autonomy of optical networks.  It discusses the
     ACTN-enhanced architecture of optical networks after the introduction
     of NMAs, including key components, interaction relationships, new
     interface requirements in the enhanced architecture, as well as
     typical use cases of agent-based autonomous operation and maintenance
     for optical networks.  The document aims to improve the autonomy
     level of optical networks and promote the realization of autonomous
     optical networks by extending the original ACTN architecture.





  Common Control and Measurement Plane                             X. Zhao
  Internet-Draft                                                     CAICT
  Intended status: Informational                                     H. Yu
  Expires: 23 April 2026                                            Huawei
                                                                     Y. Xu
                                                                     CAICT
                                                           20 October 2025


   Integration of Network Management Agent (NMA) into ACTN-Based Optical
                                  Network
               draft-zhao-ccamp-actn-optical-network-agent-00

  Abstract

     With the growth of optical network scale, the complexity of network
     operation and maintenance has increased dramatically.  Enhancing the
     intelligence level of optical network operation and management and
     building high-level autonomous optical networks have become the
     common vision of global operators.  The development of AI, especially
     large AI model technologies, provides a feasible technical path for
     realizing autonomous perception, decision-making, analysis, and
     execution.  The existing ACTN architecture provides network
     abstraction and control functions for optical networks but lacks
     higher-level autonomous capabilities.

     This document explores the introduction of AI based Network
     Management Agent(NMA) functions into ACTN-based optical networks to
     achieve high-level autonomy of optical networks.  It discusses the
     ACTN-enhanced architecture of optical networks after the introduction
     of NMAs, including key components, interaction relationships, new
     interface requirements in the enhanced architecture, as well as
     typical use cases of agent-based autonomous operation and maintenance
     for optical networks.  The document aims to improve the autonomy
     level of optical networks and promote the realization of autonomous
     optical networks by extending the original ACTN architecture.

  Discussion Venues

     This note is to be removed before publishing as an RFC.

     Discussion of this document takes place on the Network Management
     Operations Working Group mailing list (nmop@ietf.org), which is
     archived at https://mailarchive.ietf.org/arch/browse/ccamp/.

     Source for this draft and an issue tracker can be found at
     https://datatracker.ietf.org/doc/draft-zhao-ccamp-actn-optical-
     network-agent/.



  Zhao, et al.              Expires 23 April 2026                 [Page 1]


  Internet-Draft         NMA enhanced actn framework          October 2025


  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Network Management Agent (NMA) Integration",
      "description": "AI-based Network Management Agents integrated into ACTN optical networks to provide autonomous perception, decision-making, analysis, and execution capabilities. These agents extend the existing ACTN architecture with higher-level autonomous functions.",
      "type": "architecture"
    },
    {
      "title": "ACTN-Enhanced Architecture",
      "description": "Extended ACTN architecture that incorporates Network Management Agents as key components with defined interaction relationships. The enhanced architecture maintains network abstraction and control functions while adding autonomous capabilities.",
      "type": "architecture"
    },
    {
      "title": "Agent-Based Interface Requirements",
      "description": "New interface specifications required in the enhanced ACTN architecture to support communication between Network Management Agents and existing ACTN components. These interfaces enable autonomous operation and maintenance functions.",
      "type": "requirement"
    },
    {
      "title": "Autonomous Optical Network Operation",
      "description": "Use cases and patterns for agent-based autonomous operation and maintenance in optical networks. Includes scenarios where AI agents perform network management tasks without human intervention.",
      "type": "pattern"
    },
    {
      "title": "Large AI Model Integration Pattern",
      "description": "Technical approach for integrating large AI model technologies into optical network management systems. Enables autonomous network functions through AI-driven decision making processes.",
      "type": "mechanism"
    }
  ]


draft_name: draft-zhao-nmop-network-management-agent
prompt_hash: dcf7d84266035621
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:28:18.634532+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhao-nmop-network-management-agent | AI based Network Management Agent(NMA): Concepts and Architecture | 24pg
  Abstract: The evolution from Level 3 (assisted automation) to Level 4
     (autonomous self-optimization) in Autonomous Networks (AN) introduces
     requirements for Agentic capabilities, including intent-based
     reasoning, autonomous planning, and context-aware decision-making,
     which transcend the static, rule-based logic of traditional SDN
     Controllers.  This document defines the concept of the Network
     Management Agent (NMA), an AI-driven entity designed to embody these
     cognitive functions and bridge the gap between service intent and
     network operations.

     This document also specifies how the NMA utilizes the existing
     capabilities of SDN Controllers—such as topology management,
     telemetry, and enforcement—to achieve Autonomous L4 without
     duplicating policy control functions.  It further details the
     architectural integration modes and defines the interface
     requirements necessary for SDN Controllers to interoperate with NMAs.





  Network Management Operations                                    X. Zhao
  Internet-Draft                                                     CAICT
  Intended status: Informational                                   M. Wang
  Expires: 31 August 2026                                     China Mobile
                                                                     B. Wu
                                                                    Huawei
                                                             D. Ceccarelli
                                                                     Cisco
                                                                  H. Zheng
                                                                    Huawei
                                                                   J. Zhou
                                                                       ZTE
                                                          27 February 2026


     AI based Network Management Agent(NMA): Concepts and Architecture
                draft-zhao-nmop-network-management-agent-04

  Abstract

     The evolution from Level 3 (assisted automation) to Level 4
     (autonomous self-optimization) in Autonomous Networks (AN) introduces
     requirements for Agentic capabilities, including intent-based
     reasoning, autonomous planning, and context-aware decision-making,
     which transcend the static, rule-based logic of traditional SDN
     Controllers.  This document defines the concept of the Network
     Management Agent (NMA), an AI-driven entity designed to embody these
     cognitive functions and bridge the gap between service intent and
     network operations.

     This document also specifies how the NMA utilizes the existing
     capabilities of SDN Controllers—such as topology management,
     telemetry, and enforcement—to achieve Autonomous L4 without
     duplicating policy control functions.  It further details the
     architectural integration modes and defines the interface
     requirements necessary for SDN Controllers to interoperate with NMAs.

  Discussion Venues

     This note is to be removed before publishing as an RFC.

     Discussion of this document takes place on the Network Management
     Operations Working Group mailing list (nmop@ietf.org), which is
     archived at https://mailarchive.ietf.org/arch/btrse/nmop/.

     Source for this draft and an issue tracker can be found at
     https://datatracker.ietf.org/doc/draft-zhao-nmop-network-management-
     agent/.



  Zhao, et al.             Expires 31 August 2026                 [Page 1]


  Internet-Draft      Network Management Agent Concept       February 2026


  Status of This Memo

     This note is to be removed before publishing as an RFC.

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list 

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Network Management Agent (NMA)",
      "description": "An AI-driven entity that performs intent-based reasoning, autonomous planning, and context-aware decision-making to bridge service intent and network operations. Designed to achieve Level 4 autonomous self-optimization in Autonomous Networks.",
      "type": "architecture"
    },
    {
      "title": "SDN Controller Capability Utilization",
      "description": "NMA leverages existing SDN Controller functions including topology management, telemetry, and enforcement without duplicating policy control functions. Enables autonomous operation while preserving existing infrastructure investments.",
      "type": "mechanism"
    },
    {
      "title": "Level 3 to Level 4 Autonomy Evolution",
      "description": "Transition from assisted automation (Level 3) to autonomous self-optimization (Level 4) requiring agentic capabilities that transcend static rule-based logic. Defines the technical requirements for this evolutionary step in network automation.",
      "type": "requirement"
    },
    {
      "title": "NMA-SDN Controller Integration Modes",
      "description": "Architectural patterns for integrating AI-driven Network Management Agents with existing SDN Controllers. Defines multiple modes of operation to accommodate different deployment scenarios.",
      "type": "architecture"
    },
    {
      "title": "NMA-SDN Interoperability Interface Requirements",
      "description": "Technical specifications for interfaces that enable SDN Controllers to interoperate with Network Management Agents. Defines the communication protocols and data exchange formats needed for seamless integration.",
      "type": "protocol"
    }
  ]


draft_name: draft-zhao-nmrg-ai-agent-for-dtn
prompt_hash: f709cb804df0fcf6
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:28:26.563216+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhao-nmrg-ai-agent-for-dtn | AI Agent Architecture for DTN Digital Twin Network | 7pg
  Abstract: This document proposes an AI agent architecture for Digital Twin
     Network (DTN) that integrates AI agents with digital twin technology.
     The architecture extends the traditional DTN architecture by
     incorporating autonomous AI agents at each component level, enabling
     more intelligent and adaptive network management capabilities.





  nmrg                                                        J. Zhao, Ed.
  Internet-Draft                                              R. Pang, Ed.
  Intended status: Standards Track                           S. Zhang, Ed.
  Expires: 23 April 2026                                      China Unicom
                                                           20 October 2025


             AI Agent Architecture for DTN Digital Twin Network
                    draft-zhao-nmrg-ai-agent-for-dtn-00

  Abstract

     This document proposes an AI agent architecture for Digital Twin
     Network (DTN) that integrates AI agents with digital twin technology.
     The architecture extends the traditional DTN architecture by
     incorporating autonomous AI agents at each component level, enabling
     more intelligent and adaptive network management capabilities.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 23 April 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.



  Zhao, et al.              Expires 23 April 2026                 [Page 1]


  Internet-Draft        AI Agent Architecture for DTN         October 2025


  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     2.  AI Agent Architecture for Digital Twin Network  . . . . . . .   2
     3.  Architecture Components . . . . . . . . . . . . . . . . . . .   3
       3.1.  Digital Twin Network Management AI Agent  . . . . . . . .   3
       3.2.  Functional Model AI Agent . . . . . . . . . . . . . . . .   4
       3.3.  Basic Model AI Agent  . . . . . . . . . . . . . . . . . .   4
       3.4.  Data Repository AI Agent  . . . . . . . . . . . . . . . .   4
     4.  Agent Interactions  . . . . . . . . . . . . . . . . . . . . .  

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "AI Agent Architecture for DTN",
      "description": "A layered architecture that extends traditional Digital Twin Networks by incorporating autonomous AI agents at each component level. The architecture enables intelligent and adaptive network management through AI-powered decision making.",
      "type": "architecture"
    },
    {
      "title": "Digital Twin Network Management AI Agent",
      "description": "A top-level AI agent responsible for overall network management and orchestration within the digital twin environment. It coordinates high-level network policies and strategic decision making.",
      "type": "mechanism"
    },
    {
      "title": "Functional Model AI Agent",
      "description": "An AI agent that manages specific network functions and services within the digital twin network. It handles operational logic and functional behavior modeling.",
      "type": "mechanism"
    },
    {
      "title": "Basic Model AI Agent",
      "description": "A foundational AI agent that manages core network elements and basic operations. It provides fundamental network modeling and control capabilities.",
      "type": "mechanism"
    },
    {
      "title": "Data Repository AI Agent",
      "description": "An AI agent dedicated to managing data storage, retrieval, and processing within the digital twin network. It handles data lifecycle management and intelligent data operations.",
      "type": "mechanism"
    },
    {
      "title": "Multi-Level Agent Integration",
      "description": "A hierarchical integration pattern where AI agents operate at different architectural levels and interact through defined interfaces. This enables distributed intelligence across the digital twin network stack.",
      "type": "pattern"
    }
  ]


draft_name: draft-zheng-agent-identity-management
prompt_hash: 019c2ca33b9199be
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:28:31.542814+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zheng-agent-identity-management | Agent Identity Managenment | 12pg
  Abstract: This document specifies agent identity management in the Internet of
     Agents (IOA) system.  It defines the descriptive requirements for
     agent identities, the agent registration process, the structure and
     assignment of agent identifiers, and the basic and extended identity
     management functions performed by the agent gateway based on the
     agent's descriptive information.





  artarea                                                         C. Zheng
  Internet-Draft                                                    B. Liu
  Intended status: Standards Track                     Huawei Technologies
  Expires: 6 May 2026                                              N. Geng
                                                                    Huawei
                                                                    Q. Gao
                                                                  X. Shang
                                                                     Z. Li
                                                       Huawei Technologies
                                                           2 November 2025


                         Agent Identity Managenment
                  draft-zheng-agent-identity-management-00

  Abstract

     This document specifies agent identity management in the Internet of
     Agents (IOA) system.  It defines the descriptive requirements for
     agent identities, the agent registration process, the structure and
     assignment of agent identifiers, and the basic and extended identity
     management functions performed by the agent gateway based on the
     agent's descriptive information.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 6 May 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.






  Zheng, et al.              Expires 6 May 2026                   [Page 1]


  Internet-Draft         Agent Identity Managenment          November 2025


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
       1.1.  Requirements Language . . . . . . . . . . . . . . . . . .   3
     2.  Overview of the Agent Ident

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Agent Identity Descriptive Requirements",
      "description": "Defines specific requirements for describing agent identities in the Internet of Agents (IOA) system. These requirements specify what information must be captured to properly identify and characterize agents.",
      "type": "requirement"
    },
    {
      "title": "Agent Registration Process",
      "description": "Specifies the process by which agents register themselves within the IOA system. This includes the steps and procedures for onboarding new agents and establishing their identities.",
      "type": "protocol"
    },
    {
      "title": "Agent Identifier Structure and Assignment",
      "description": "Defines the structure of agent identifiers and the mechanism for assigning unique identifiers to agents. This ensures each agent has a distinct identity within the IOA system.",
      "type": "mechanism"
    },
    {
      "title": "Agent Gateway Identity Management Functions",
      "description": "Specifies basic and extended identity management functions performed by the agent gateway based on agent descriptive information. The gateway serves as a central component for managing agent identities.",
      "type": "architecture"
    }
  ]


draft_name: draft-zheng-dispatch-agent-identity-management
prompt_hash: c475c643c4848b7c
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:28:37.938611+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zheng-dispatch-agent-identity-management | Agent Identity Managenment | 12pg
  Abstract: This document specifies agent identity management in the Internet of
     Agents (IOA) system.  It defines the descriptive requirements for
     agent identities, the agent registration process, the structure and
     assignment of agent identifiers, and the basic and extended identity
     management functions performed by the agent gateway based on the
     agent's descriptive information.





  Dispatch                                                        C. Zheng
  Internet-Draft                                                    B. Liu
  Intended status: Standards Track                                 N. Geng
  Expires: 7 May 2026                                               Q. Gao
                                                                  X. Shang
                                                                     Z. Li
                                                       Huawei Technologies
                                                           3 November 2025


                         Agent Identity Managenment
             draft-zheng-dispatch-agent-identity-management-00

  Abstract

     This document specifies agent identity management in the Internet of
     Agents (IOA) system.  It defines the descriptive requirements for
     agent identities, the agent registration process, the structure and
     assignment of agent identifiers, and the basic and extended identity
     management functions performed by the agent gateway based on the
     agent's descriptive information.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 7 May 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights



  Zheng, et al.              Expires 7 May 2026                   [Page 1]


  Internet-Draft         Agent Identity Managenment          November 2025


     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
       1.1.  Requirements Language . . . . . . . . . . . . . . . . . .   3
     2.  Overview of the Agent Identity Management . . . . . . . . . .   3
     3.  Agent description Requirements  . . . . . . . . . . . . . . .   4
       3.1.  Basic Information . .

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Agent Identifier Structure",
      "description": "Defines the structure and assignment process for unique identifiers used to distinguish agents in the Internet of Agents (IOA) system. The identifiers enable routing and addressing of agents within the distributed system.",
      "type": "mechanism"
    },
    {
      "title": "Agent Registration Process",
      "description": "Specifies the process by which agents register themselves with the system to establish their identity and capabilities. This process creates the binding between agent identifiers and their descriptive information.",
      "type": "protocol"
    },
    {
      "title": "Agent Gateway Identity Management",
      "description": "Defines basic and extended identity management functions performed by agent gateways based on agent descriptive information. These functions include identity verification, capability tracking, and access control.",
      "type": "architecture"
    },
    {
      "title": "Agent Descriptive Requirements",
      "description": "Establishes requirements for how agents must describe themselves including basic information and capabilities. This standardizes the metadata needed for effective agent discovery and interaction.",
      "type": "requirement"
    },
    {
      "title": "Internet of Agents Identity Framework",
      "description": "Provides an overarching framework for managing identities across a distributed system of autonomous agents. The framework enables scalable identity management in multi-agent environments.",
      "type": "architecture"
    }
  ]


draft_name: draft-zhul-dhc-bnc-up-specific-suboption
prompt_hash: 7de2d2e22549a768
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:28:44.139980+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhul-dhc-bnc-up-specific-suboption | Broadband Network UP-Specific Information Suboption for the DHCP Relay Agent Option | 6pg
  Abstract: This document defines a new Broadband Network UP-Specific Information
     suboption for the Dynamic Host Configuration Protocol’s (DHCP) relay
     agent information option.  The suboption allows the DHCP relay agent
     (Broadband Network CP) to include UP-specific information in the DHCP
     messages it forwards, to ensure that subscribers within the same SGRP
     under the same UP are assigned IP addresses from the same address
     space by the DHCP server.





  dhc                                                          L. Zhu, Ed.
  Internet-Draft                                             Y. Zhang, Ed.
  Intended status: Standards Track                            China Unicom
  Expires: 31 July 2026                                    27 January 2026


   Broadband Network UP-Specific Information Suboption for the DHCP Relay
                                Agent Option
                draft-zhul-dhc-bnc-up-specific-suboption-01

  Abstract

     This document defines a new Broadband Network UP-Specific Information
     suboption for the Dynamic Host Configuration Protocol’s (DHCP) relay
     agent information option.  The suboption allows the DHCP relay agent
     (Broadband Network CP) to include UP-specific information in the DHCP
     messages it forwards, to ensure that subscribers within the same SGRP
     under the same UP are assigned IP addresses from the same address
     space by the DHCP server.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 31 July 2026.

  Copyright Notice

     Copyright (c) 2026 IETF Trust and the persons identified as the
     document authors.  All rights reserved.










  Zhu & Zhang               Expires 31 July 2026                  [Page 1]


  Internet-Draft  Broadband Network UP-Specific Informatio    January 2026


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     2.  Conventions and Definitions . . . . . . . . . . . . . . . . .   3
     3.  Broadband Network UP-Specific Information Suboption . . . . .   4
     4.  DHCP Relay Agent Behavior . . . . . . . . . . . . . . . . . .   5
     5.  DHCP Server Behavior  . . . . . . . . . . . . . . . . . . . .   5
     6.  Security Considerations . . . . . . . . . . . . . . . . . . .   5
     7.  IANA Considerations . . . . 

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "UP-Specific Information Suboption",
      "description": "A new DHCP relay agent suboption that carries UP (User Plane) specific information to enable proper address assignment. Allows broadband network control plane to include UP context in forwarded DHCP messages.",
      "type": "extension"
    },
    {
      "title": "SGRP Address Space Consistency",
      "description": "Mechanism to ensure subscribers within the same SGRP (Subscriber Group) under the same UP are assigned IP addresses from the same address space. Provides address allocation consistency based on network topology.",
      "type": "mechanism"
    },
    {
      "title": "Broadband Network CP Relay Enhancement",
      "description": "Extension to DHCP relay agent behavior for broadband network control plane functions. Enables relay agents to inject UP-specific context into DHCP message flows.",
      "type": "extension"
    },
    {
      "title": "UP-Aware DHCP Server Processing",
      "description": "Server-side behavior modification to process UP-specific information from relay agents. Enables DHCP servers to make topology-aware address assignment decisions.",
      "type": "mechanism"
    }
  ]


draft_name: draft-zhul-intarea-bnc-up-specific-suboption
prompt_hash: cc2fbb459d4b00ce
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:28:50.577735+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zhul-intarea-bnc-up-specific-suboption | Broadband Network UP-Specific Information Suboption for the DHCP Relay Agent Option | 6pg
  Abstract: This document defines a new Broadband Network UP-Specific Information
     suboption for the Dynamic Host Configuration Protocol’s (DHCP) relay
     agent information option.  The suboption allows the DHCP relay agent
     (Broadband Network CP) to include UP-specific information in the DHCP
     messages it forwards, to ensure that subscribers within the same SGRP
     under the same UP are assigned IP addresses from the same address
     space by the DHCP server.





  intarea                                                      L. Zhu, Ed.
  Internet-Draft                                             Y. Zhang, Ed.
  Intended status: Standards Track                            China Unicom
  Expires: 16 August 2026                                 12 February 2026


   Broadband Network UP-Specific Information Suboption for the DHCP Relay
                                Agent Option
              draft-zhul-intarea-bnc-up-specific-suboption-00

  Abstract

     This document defines a new Broadband Network UP-Specific Information
     suboption for the Dynamic Host Configuration Protocol’s (DHCP) relay
     agent information option.  The suboption allows the DHCP relay agent
     (Broadband Network CP) to include UP-specific information in the DHCP
     messages it forwards, to ensure that subscribers within the same SGRP
     under the same UP are assigned IP addresses from the same address
     space by the DHCP server.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 16 August 2026.

  Copyright Notice

     Copyright (c) 2026 IETF Trust and the persons identified as the
     document authors.  All rights reserved.










  Zhu & Zhang              Expires 16 August 2026                 [Page 1]


  Internet-Draft  Broadband Network UP-Specific Informatio   February 2026


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     2.  Conventions and Definitions . . . . . . . . . . . . . . . . .   3
     3.  Broadband Network UP-Specific Information Suboption . . . . .   4
     4.  DHCP Relay Agent Behavior . . . . . . . . . . . . . . . . . .   5
     5.  DHCP Server Behavior  . . . . . . . . . . . . . . . . . . . .   5
     6.  Security Considerations . . . . . . . . . . . . . . . . . . .   5
     7.  IANA Considerations . . 

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Broadband Network UP-Specific Information Suboption",
      "description": "A new DHCP relay agent suboption that carries UP-specific information to help DHCP servers make informed IP address assignment decisions. This extends the existing DHCP relay agent information option with broadband network context.",
      "type": "extension"
    },
    {
      "title": "SGRP Address Space Consistency Mechanism",
      "description": "Ensures that subscribers within the same Service Group (SGRP) under the same User Plane (UP) receive IP addresses from the same address space. This maintains network topology consistency for broadband subscribers.",
      "type": "mechanism"
    },
    {
      "title": "Broadband Network CP as DHCP Relay Agent",
      "description": "Defines the role of Broadband Network Control Plane (CP) as a DHCP relay agent that includes UP-specific information in forwarded DHCP messages. This creates a bridge between broadband network architecture and DHCP operations.",
      "type": "architecture"
    },
    {
      "title": "UP-Aware DHCP Server Behavior",
      "description": "Specifies how DHCP servers should process and utilize UP-specific information from relay agents to make address assignment decisions. This enables DHCP servers to understand broadband network topology.",
      "type": "protocol"
    }
  ]


draft_name: draft-zl-agents-networking-architecture
prompt_hash: 867843c96e4111e9
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:28:57.886387+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zl-agents-networking-architecture | Agents Networking Architecture for Enterprise and Broadband | 13pg
  Abstract: This document introduces agents networking architecture and defines
     the core components of agent networking, as well as typical
     interactions among these key components.





  network working group                                           L. Zhang
  Internet-Draft                                                    B. Liu
  Intended status: Informational                       Huawei Technologies
  Expires: 23 April 2026                                           N. Geng
                                                                    Huawei
                                                                   Z. Wang
                                                               Independent
                                                           20 October 2025


        Agents Networking Architecture for Enterprise and Broadband
                 draft-zl-agents-networking-architecture-00

  Abstract

     This document introduces agents networking architecture and defines
     the core components of agent networking, as well as typical
     interactions among these key components.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 23 April 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.











  Zhang, et al.             Expires 23 April 2026                 [Page 1]


  Internet-Draft       Agents Networking Architecture         October 2025


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
       1.1.  Requirements Language . . . . . . . . . . . . . . . . . .   3
     2.  IoA architecture and Components . . . . . . . . . . . . . . .   3
       2.1.  Overview of Agents Networking . . . . . . . . . . . . . .   3
       2.2.  Agent Certificate Authority . . . . . . . . . . . . . . .   4
       2.3.  Agent Registration Server . . . . . . . . . . . . . . . .   4
       2.4.  AI Agents . . . . . . . . . . . . . . . . . . . . . . . .   5


  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Agent Certificate Authority",
      "description": "A specialized certificate authority component designed specifically for managing digital certificates and authentication within agent networking environments. It provides security infrastructure for AI agents operating in enterprise and broadband networks.",
      "type": "architecture"
    },
    {
      "title": "Agent Registration Server",
      "description": "A centralized server component that handles the registration and management of AI agents within the networking architecture. It maintains agent identity and facilitates agent discovery and coordination.",
      "type": "architecture"
    },
    {
      "title": "IoA Architecture",
      "description": "Internet of Agents architecture that defines the structural framework for connecting and coordinating multiple AI agents across enterprise and broadband networks. It establishes the foundational components and their relationships.",
      "type": "architecture"
    },
    {
      "title": "Agent-to-Agent Interaction Model",
      "description": "A communication pattern that defines how AI agents interact with each other within the networking architecture. It specifies the protocols and mechanisms for inter-agent coordination and data exchange.",
      "type": "pattern"
    },
    {
      "title": "Agents Networking Core Components",
      "description": "A set of essential building blocks including Agent Certificate Authority, Agent Registration Server, and AI Agents that form the foundation of the agent networking system. These components work together to enable secure agent communication and coordination.",
      "type": "architecture"
    }
  ]


draft_name: draft-zl-agents-networking-framework
prompt_hash: 77b01c4c6f1e70a6
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:28:56.518249+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zl-agents-networking-framework | Agents Networking Framework for Enterprise and Broadband | 14pg
  Abstract: This document introduces agents networking framework and defines the
     core components of agent networking in enterprise and broadband, as
     well as typical interactions among these key components.





  rtgwg                                                           L. Zhang
  Internet-Draft                                                    B. Liu
  Intended status: Informational                                   N. Geng
  Expires: 6 May 2026                                             X. Shang
                                                                    Q. Gao
                                                                     Z. Li
                                                       Huawei Technologies
                                                           2 November 2025


          Agents Networking Framework for Enterprise and Broadband
                  draft-zl-agents-networking-framework-00

  Abstract

     This document introduces agents networking framework and defines the
     core components of agent networking in enterprise and broadband, as
     well as typical interactions among these key components.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 6 May 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.











  Zhang, et al.              Expires 6 May 2026                   [Page 1]


  Internet-Draft         Agents Networking Framework         November 2025


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
       1.1.  Requirements Language . . . . . . . . . . . . . . . . . .   3
     2.  IoA framework and Components  . . . . . . . . . . . . . . . .   3
       2.1.  Overview of Agents Networking . . . . . . . . . . . . . .   3
       2.2.  Agent Certificate Authority . . . . . . . . . . . . . . .   4
       2.3.  Agent Registration Server . . . . . . . . . . . . . . . .   4
       2.4.  AI Agents . . . . . . . . . . . . . . . . .

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "IoA Framework",
      "description": "Internet of Agents (IoA) framework defining core components for agent networking in enterprise and broadband environments. Establishes the overall architecture for agent-based networking systems.",
      "type": "architecture"
    },
    {
      "title": "Agent Certificate Authority",
      "description": "Dedicated certificate authority component for managing authentication and security credentials for AI agents in the networking framework. Provides trust establishment mechanisms for agent communications.",
      "type": "mechanism"
    },
    {
      "title": "Agent Registration Server",
      "description": "Centralized server component responsible for registering and managing AI agents within the networking framework. Handles agent discovery and lifecycle management.",
      "type": "mechanism"
    },
    {
      "title": "Multi-Agent Communication Pattern",
      "description": "Defines typical interactions and communication patterns among key components in the agents networking framework. Establishes standardized methods for agent-to-agent and agent-to-infrastructure communications.",
      "type": "pattern"
    }
  ]


draft_name: draft-zl-agents-networking-scenarios
prompt_hash: 179ea9e369a5c0b1
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:29:05.918240+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zl-agents-networking-scenarios | Agents Networking Scenarios in Enterprise and Broadband Networks | 8pg
  Abstract: This document describes agents networking scenarios in enterprise and
     home broadband networks.  These scenarios differ from 6G and Internet
     scenarios.  Since the agentic service is still at the emerging stage,
     especially in enterprise and home broadband networks, the scenarios
     are mostly based on reasonable assumptions.





  network working group                                             B. Liu
  Internet-Draft                                                  L. Zhang
  Intended status: Informational                       Huawei Technologies
  Expires: 23 April 2026                                            Y. Liu
                                                               Independent
                                                           20 October 2025


      Agents Networking Scenarios in Enterprise and Broadband Networks
                  draft-zl-agents-networking-scenarios-00

  Abstract

     This document describes agents networking scenarios in enterprise and
     home broadband networks.  These scenarios differ from 6G and Internet
     scenarios.  Since the agentic service is still at the emerging stage,
     especially in enterprise and home broadband networks, the scenarios
     are mostly based on reasonable assumptions.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 23 April 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.











  Liu, et al.               Expires 23 April 2026                 [Page 1]


  Internet-Draft         Agents Networking Scenarios          October 2025


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
       1.1.  Requirements Language . . . . . . . . . . . . . . . . . .   2
     2.  Enterprise Scenarios  . . . . . . . . . . . . . . . . . . . .   3
       2.1.  Smart Office  . . . . . . . . . . . . . . . . . . . . . .   3
       2.2.  Agentic Digitalization  . . . . . . . . . . . . . . . . .   3
       2.3.  Industrial Automation . . . . . . . . . . . . . . . . . .   4
     3.  Home Broadband Network Scenarios  . . . . . . . . . 

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Smart Office Agent Coordination",
      "description": "Agents deployed across office environments to coordinate meeting room management, resource allocation, and workplace optimization. These agents operate within enterprise network constraints and security boundaries.",
      "type": "architecture"
    },
    {
      "title": "Agentic Digitalization Framework",
      "description": "Enterprise digitalization processes automated through networked agents that handle document processing, workflow management, and business process automation. Requires specific networking protocols for agent-to-agent communication in enterprise environments.",
      "type": "mechanism"
    },
    {
      "title": "Industrial Automation Agent Networks",
      "description": "Specialized agent networking for industrial control systems and manufacturing automation. Agents coordinate production processes and equipment management with real-time networking requirements.",
      "type": "architecture"
    },
    {
      "title": "Home Broadband Agent Scenarios",
      "description": "Agent deployment patterns specific to residential broadband networks, differing from enterprise scenarios in terms of bandwidth, security models, and device types. Addresses home automation and personal assistant coordination.",
      "type": "pattern"
    },
    {
      "title": "Enterprise vs Internet Agent Networking",
      "description": "Distinct networking requirements and scenarios for agents in controlled enterprise environments compared to open Internet deployments. Focuses on security boundaries and network topology constraints.",
      "type": "requirement"
    }
  ]


draft_name: draft-zlgsgl-rtgwg-agents-networking-framework
prompt_hash: 86f7897645a40afd
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:29:11.879336+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zlgsgl-rtgwg-agents-networking-framework | Agents Networking Framework for Enterprise and Broadband | 14pg
  Abstract: This document introduces agents networking framework and defines the
     core components of agent networking in enterprise and broadband, as
     well as typical interactions among these key components.





  rtgwg                                                           L. Zhang
  Internet-Draft                                                    B. Liu
  Intended status: Informational                                   N. Geng
  Expires: 7 May 2026                                             X. Shang
                                                                    Q. Gao
                                                                     Z. Li
                                                       Huawei Technologies
                                                           3 November 2025


          Agents Networking Framework for Enterprise and Broadband
             draft-zlgsgl-rtgwg-agents-networking-framework-00

  Abstract

     This document introduces agents networking framework and defines the
     core components of agent networking in enterprise and broadband, as
     well as typical interactions among these key components.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 7 May 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.











  Zhang, et al.              Expires 7 May 2026                   [Page 1]


  Internet-Draft         Agents Networking Framework         November 2025


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
       1.1.  Requirements Language . . . . . . . . . . . . . . . . . .   3
     2.  IoA framework and Components  . . . . . . . . . . . . . . . .   3
       2.1.  Overview of Agents Networking . . . . . . . . . . . . . .   3
       2.2.  Agent Certificate Authority . . . . . . . . . . . . . . .   4
       2.3.  Agent Registration Server . . . . . . . . . . . . . . . .   4
       2.4.  AI Agents . . . . . . . . . . . . . . 

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Agent Certificate Authority",
      "description": "A centralized authority component responsible for issuing and managing digital certificates for AI agents in the networking framework. This enables secure authentication and authorization of agents within enterprise and broadband networks.",
      "type": "architecture"
    },
    {
      "title": "Agent Registration Server",
      "description": "A server component that handles the registration and lifecycle management of AI agents in the network. It maintains agent identities, capabilities, and status information for the networking framework.",
      "type": "architecture"
    },
    {
      "title": "IoA Framework",
      "description": "Internet of Agents framework that defines the overall structure and interactions for agent-based networking in enterprise and broadband environments. It establishes the foundational architecture for agent communication and coordination.",
      "type": "architecture"
    },
    {
      "title": "Agents Networking",
      "description": "A networking paradigm that enables AI agents to interact and collaborate within network infrastructure. It defines how multiple agents can work together to manage and optimize enterprise and broadband network operations.",
      "type": "pattern"
    }
  ]


draft_name: draft-zm-rtgwg-mcp-troubleshooting
prompt_hash: a8fbd8a42f6ce480
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:29:18.639949+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zm-rtgwg-mcp-troubleshooting | Using the Model Context Protocol (MCP) for Intent-Based Network Troubleshooting Automation | 15pg
  Abstract: The Model Context Protocol (MCP) is an open standard that enables
     Large Language Model (LLM) applications to seamlessly integrate with
     external data sources and tools by exposing Resources, Prompts and
     Tools in a JSON-RPC 2.0 transport.  This document describes a mapping
     of MCP roles, primitives and security model to the network management
     domain so that network devices act as MCP servers and network
     controllers act as MCP clients.  This document also extends the model
     to Device-to-Device (D2D) collaboration, allowing network elements to
     perform distributed fault correlation when the controller is
     unreachable or when real-time cross-device data is required.  The
     goal is to provide an intent-based, conversational and secure
     approach for automated network troubleshooting, configuration
     validation, and closed-loop remediation without inventing new
     protocols or device agents.





  Network Working Group                                            G. Zeng
  Internet-Draft                                                    J. Mao
  Intended status: Informational                                    B. Liu
  Expires: 6 May 2026                                              N. Geng
                                                                  X. Shang
                                                                    Q. Gao
                                                                     Z. Li
                                                                    Huawei
                                                           2 November 2025


      Using the Model Context Protocol (MCP) for Intent-Based Network
                         Troubleshooting Automation
                   draft-zm-rtgwg-mcp-troubleshooting-01

  Abstract

     The Model Context Protocol (MCP) is an open standard that enables
     Large Language Model (LLM) applications to seamlessly integrate with
     external data sources and tools by exposing Resources, Prompts and
     Tools in a JSON-RPC 2.0 transport.  This document describes a mapping
     of MCP roles, primitives and security model to the network management
     domain so that network devices act as MCP servers and network
     controllers act as MCP clients.  This document also extends the model
     to Device-to-Device (D2D) collaboration, allowing network elements to
     perform distributed fault correlation when the controller is
     unreachable or when real-time cross-device data is required.  The
     goal is to provide an intent-based, conversational and secure
     approach for automated network troubleshooting, configuration
     validation, and closed-loop remediation without inventing new
     protocols or device agents.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 6 May 2026.



  Zeng, et al.               Expires 6 May 2026                   [Page 1]


  Internet-Draft              MCP for Networks               November 2025


  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review thes

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "MCP Role Mapping for Network Management",
      "description": "Maps Model Context Protocol client-server roles to network architecture where network devices act as MCP servers and network controllers act as MCP clients. This enables LLM applications to interact with network infrastructure through standardized JSON-RPC 2.0 transport.",
      "type": "architecture"
    },
    {
      "title": "Device-to-Device MCP Extension",
      "description": "Extends MCP to support direct Device-to-Device (D2D) collaboration for distributed fault correlation when controllers are unreachable or real-time cross-device data is required. Allows network elements to perform autonomous troubleshooting without central coordination.",
      "type": "extension"
    },
    {
      "title": "MCP Primitives for Network Operations",
      "description": "Adapts MCP's Resources, Prompts and Tools primitives to network management domain for exposing device state, troubleshooting workflows, and network operations. Enables intent-based conversational interface for network automation.",
      "type": "mechanism"
    },
    {
      "title": "LLM-Driven Network Troubleshooting Framework",
      "description": "Provides automated network troubleshooting, configuration validation, and closed-loop remediation through LLM integration without requiring new protocols or device agents. Leverages existing MCP standard for AI-driven network operations.",
      "type": "protocol"
    }
  ]


draft_name: draft-zyyhl-agent-networks-framework
prompt_hash: e9f8514605ae484d
model: claude-sonnet-4-20250514
created_at: 2026-02-28T11:29:23.861696+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zyyhl-agent-networks-framework | Framework for AI Agent Networks | 21pg
  Abstract: This document defines the framework of AI agent networks based on
     Agent Network Protocol (ANP) protocol.  [ANP] It provides the basic
     functions that needs to support AI agent communication in the AI
     agent networks within the trust domain.





  Network Working Group                                            Y. Zhou
  Internet-Draft                                 ANP Open Source Community
  Intended status: Informational                                    K. Yao
  Expires: 23 April 2026                                      China Mobile
                                                                     M. Yu
                                                             China Telecom
                                                                    M. Han
                                                              China Unicom
                                                                     C. Li
                                                                    Huawei
                                                           20 October 2025


                      Framework for AI Agent Networks
                  draft-zyyhl-agent-networks-framework-01

  Abstract

     This document defines the framework of AI agent networks based on
     Agent Network Protocol (ANP) protocol.  [ANP] It provides the basic
     functions that needs to support AI agent communication in the AI
     agent networks within the trust domain.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 23 April 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.

     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.



  Zhou, et al.              Expires 23 April 2026                 [Page 1]


  Internet-Draft          Agent Networks Framework            October 2025


     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
       1.1.  Overview  . . . . . . . . . . . . . . . . . . . . . . . .   3
       1.2.  Scope . . . . . . . . . . . . . . . . . . . . . . . . . .   3
       1.3.  Requirements

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Agent Network Protocol (ANP)",
      "description": "A specific protocol designed to enable communication between AI agents within network environments. ANP serves as the foundational communication mechanism for AI agent networks.",
      "type": "protocol"
    },
    {
      "title": "Trust Domain-Based Agent Networks",
      "description": "An architectural approach that constrains AI agent communication within defined trust boundaries. This mechanism ensures secure and controlled agent interactions within trusted network segments.",
      "type": "architecture"
    },
    {
      "title": "AI Agent Communication Framework",
      "description": "A structured framework that defines the basic functions and mechanisms required for AI agents to communicate effectively in networked environments. It provides standardized communication patterns for agent-to-agent interactions.",
      "type": "framework"
    }
  ]


draft_name: draft-yang-nmrg-mcp-nm
prompt_hash: 156abf309346a245
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:40:35.510809+00:00
response_json:
  {"name": "draft-yang-nmrg-mcp-nm", "s": "Applies Model Context Protocol (MCP) to network management for AI integration. Discusses network exposure, MCP server discovery, and communication between network elements and controllers.", "n": 3, "nn": "Moderate novelty in applying MCP to network management, but builds on established concepts", "m": 2, "mn": "Early stage draft with broad scope but limited concrete technical details", "o": 4, "on": "Significant overlap with other MCP network management drafts in this set", "mo": 2, "mon": "Limited momentum indicated by single draft and broad approach", "r": 4, "rn": "Highly relevant to AI-driven network operations and autonomous networking", "c": ["Autonomous netops", "A2A protocols", "Agent discovery/reg"]}


draft_name: draft-zeng-mcp-network-measurement
prompt_hash: 360efaef996d8d4d
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:40:35.535516+00:00
response_json:
  {"name": "draft-zeng-mcp-network-measurement", "s": "Proposes MCP framework for intelligent network measurement with AI assistance. Enables natural language-driven network monitoring and fault diagnosis.", "n": 4, "nn": "Novel application of MCP to specific network measurement domain with natural language interface", "m": 3, "mn": "Reasonable maturity with concrete use cases but still developing technical details", "o": 3, "on": "Some overlap with general MCP network management but focuses on measurement", "mo": 3, "mon": "Moderate momentum with focused application area and multiple related drafts by author", "r": 4, "rn": "Very relevant for AI-assisted network operations and intelligent monitoring", "c": ["Autonomous netops", "Human-agent interaction", "ML traffic mgmt"]}


draft_name: draft-zw-rtgwg-mcp-network-mgmt
prompt_hash: 76be511b96a4e5d2
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:40:35.545095+00:00
response_json:
  {"name": "draft-zw-rtgwg-mcp-network-mgmt", "s": "Specifies MCP extensions for network equipment management with routers/switches as MCP servers. Defines capability tokens, tools, and error codes without breaking existing MCP.", "n": 3, "nn": "Incremental novelty in extending MCP for network equipment with backward compatibility", "m": 4, "mn": "Good maturity with concrete technical specifications and implementation details", "o": 4, "on": "Heavy overlap with draft-zeng-mcp-network-mgmt, nearly identical abstracts", "mo": 3, "mon": "Moderate momentum with detailed technical approach and routing working group focus", "r": 4, "rn": "Highly relevant for network equipment AI integration and management", "c": ["Autonomous netops", "A2A protocols", "Data formats/interop"]}


draft_name: draft-howe-sipcore-mcp-extension
prompt_hash: 0f28c2afac61a585
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:40:35.554808+00:00
response_json:
  {"name": "draft-howe-sipcore-mcp-extension", "s": "Defines SIP extension to carry Model Context Protocol with new option-tags, headers, and media types. Enables MCP payload exchange during SIP sessions.", "n": 4, "nn": "Novel integration of MCP with SIP protocol, unique approach among the drafts", "m": 4, "mn": "High maturity with detailed protocol specifications and substantial length", "o": 1, "on": "Unique approach focusing on SIP integration rather than network management", "mo": 3, "mon": "Solid momentum with comprehensive specification and established SIP community", "r": 3, "rn": "Moderately relevant to AI agents in communication systems but different domain", "c": ["A2A protocols", "Data formats/interop", "Agent discovery/reg"]}


draft_name: draft-zeng-mcp-network-mgmt
prompt_hash: e5be3a1d8496be1c
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:40:35.573162+00:00
response_json:
  {"name": "draft-zeng-mcp-network-mgmt", "s": "Specifies MCP extensions for network equipment management allowing routers/switches as MCP servers. Defines capability tokens, tools, and error codes with backward compatibility.", "n": 3, "nn": "Similar approach to network MCP extensions as other drafts in this area", "m": 2, "mn": "Lower maturity with brief specification and limited technical detail", "o": 5, "on": "Extremely heavy overlap with draft-zw-rtgwg-mcp-network-mgmt, nearly identical", "mo": 2, "mon": "Lower momentum due to brevity and potential duplication with other efforts", "r": 4, "rn": "Highly relevant for AI-driven network management despite overlap issues", "c": ["Autonomous netops", "A2A protocols", "Data formats/interop"]}


draft_name: draft-zm-rtgwg-mcp-network-measurement
prompt_hash: 3bf3cdd9fa2b7954
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:40:50.845606+00:00
response_json:
  {"name": "draft-zm-rtgwg-mcp-network-measurement", "s": "Proposes using Model Context Protocol to enable AI-driven network measurement operations. Network devices act as MCP servers while controllers with LLM capability serve as clients for natural language-driven monitoring.", "n": 3, "nn": "Novel application of MCP to network measurement, but builds on established concepts", "m": 2, "mn": "Early stage work, 10 pages suggests preliminary development", "o": 4, "on": "High overlap with other MCP network management drafts in this set", "mo": 2, "mon": "Limited momentum indicators, newer draft with narrow focus", "r": 3, "rn": "Relevant to autonomous network operations but specific to measurement domain", "c": ["Autonomous netops", "A2A protocols", "Human-agent interaction"]}


draft_name: draft-zw-nmrg-mcp-network-mgmt
prompt_hash: fefd7d30b3d4363b
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:40:50.866812+00:00
response_json:
  {"name": "draft-zw-nmrg-mcp-network-mgmt", "s": "Defines MCP extensions for network equipment management using JSON-RPC 2.0 framework. Specifies how network devices can act as MCP servers with controllers as clients.", "n": 3, "nn": "Practical extension of existing MCP protocol to networking domain", "m": 3, "mn": "More mature at 18 pages with detailed technical specifications", "o": 5, "on": "Nearly identical to draft-zw-opsawg-mcp-network-mgmt", "r": 4, "rn": "Highly relevant to autonomous network management and AI-driven operations", "c": ["Autonomous netops", "A2A protocols", "Data formats/interop"]}


draft_name: draft-mcp-over-moqt
prompt_hash: c573a93ca2728ed5
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:40:50.878839+00:00
response_json:
  {"name": "draft-mcp-over-moqt", "s": "Defines transport mapping for Model Context Protocol over Media over QUIC Transport. Specifies how MCP messages map to MOQT objects for efficient delivery.", "n": 4, "nn": "Novel transport combination addressing efficiency needs of MCP", "m": 4, "mn": "Well-developed at 32 pages with detailed protocol specifications", "o": 5, "on": "Identical to draft-jennings-mcp-over-moqt", "mo": 3, "mon": "Moderate momentum, addresses important transport layer needs", "r": 3, "rn": "Foundational transport work relevant to broader AI agent communication", "c": ["A2A protocols", "Data formats/interop"]}


draft_name: draft-jennings-mcp-over-moqt
prompt_hash: f3647fb2f6e2da36
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:40:50.890438+00:00
response_json:
  {"name": "draft-jennings-mcp-over-moqt", "s": "Defines transport mapping for Model Context Protocol over Media over QUIC Transport. Specifies how MCP messages map to MOQT objects for efficient delivery.", "n": 4, "nn": "Novel transport combination addressing efficiency needs of MCP", "m": 4, "mn": "Well-developed at 32 pages with detailed protocol specifications", "o": 5, "on": "Identical to draft-mcp-over-moqt", "mo": 3, "mon": "Moderate momentum, Jennings authorship suggests established backing", "r": 3, "rn": "Foundational transport work relevant to broader AI agent communication", "c": ["A2A protocols", "Data formats/interop"]}


draft_name: draft-zw-opsawg-mcp-network-mgmt
prompt_hash: 889098891448bb85
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:40:50.900759+00:00
response_json:
  {"name": "draft-zw-opsawg-mcp-network-mgmt", "s": "Defines MCP extensions for network equipment management using JSON-RPC 2.0 framework. Specifies how network devices can act as MCP servers with controllers as clients.", "n": 3, "nn": "Practical extension of existing MCP protocol to networking domain", "m": 3, "mn": "More mature at 18 pages, updated version suggests active development", "o": 5, "on": "Nearly identical to draft-zw-nmrg-mcp-network-mgmt, likely venue change", "mo": 3, "mon": "Active development shown by venue migration and updates", "r": 4, "rn": "Highly relevant to autonomous network management and AI-driven operations", "c": ["Autonomous netops", "A2A protocols", "Data formats/interop"]}


draft_name: draft-jennings-ai-mcp-over-moq
prompt_hash: 382ced7c72c7bc08
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:11.322435+00:00
response_json:
  {"name": "draft-jennings-ai-mcp-over-moq", "s": "Defines how to transport Model Context Protocol (MCP) messages over Media over QUIC Transport (MOQT) for AI agent communication. Focuses on efficient delivery of agent skills with progressive loading and caching.", "n": 4, "nn": "Novel combination of MCP and MOQT with emphasis on agent skills delivery", "m": 4, "mn": "Well-structured 37-page specification with detailed transport mappings", "o": 2, "on": "Some overlap with general agent communication but unique transport focus", "mo": 4, "mon": "Strong technical foundation building on established protocols", "r": 4, "rn": "High relevance for scalable AI agent communication infrastructure", "c": ["A2A protocols", "Data formats/interop", "Model serving/inference"]}


draft_name: draft-chuyi-nmrg-agentic-network-inference
prompt_hash: 133f567e89324dd6
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:11.348291+00:00
response_json:
  {"name": "draft-chuyi-nmrg-agentic-network-inference", "s": "Proposes network architecture for multi-agent interconnection and multi-level inference across cloud-edge-end environments. Addresses coordination and scheduling for collaborative agent tasks.", "n": 3, "nn": "Addresses emerging need for agent interconnection but concepts are broad", "m": 2, "mn": "Short 9-page draft with high-level concepts, needs more technical detail", "o": 3, "on": "Moderate overlap with general distributed AI and edge computing work", "mo": 3, "mon": "Timely topic but execution needs strengthening", "r": 4, "rn": "Very relevant to future agent-centric network architectures", "c": ["Autonomous netops", "Model serving/inference", "A2A protocols"]}


draft_name: draft-bernardos-nmrg-agentic-network-optimization
prompt_hash: dacea4bd0bcfe58b
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:11.358755+00:00
response_json:
  {"name": "draft-bernardos-nmrg-agentic-network-optimization", "s": "Focuses on agentic AI for distributed sensing in ISAC networks with joint optimization of sensing and communication. Addresses synchronization and processing constraints for multi-sensor fusion.", "n": 4, "nn": "Specific application of agentic AI to ISAC sensing optimization", "m": 3, "mn": "14 pages with good technical depth but appears incomplete in abstract", "o": 3, "on": "Some overlap with general network optimization but ISAC focus is distinctive", "mo": 3, "mon": "ISAC is hot topic but agentic angle needs clearer positioning", "r": 3, "rn": "Relevant for specific sensing applications but narrower scope", "c": ["Autonomous netops", "ML traffic mgmt", "Other AI/agent"]}


draft_name: draft-jadoon-nmrg-agentic-ai-autonomous-networks
prompt_hash: bf43f3233c61377d
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:11.368447+00:00
response_json:
  {"name": "draft-jadoon-nmrg-agentic-ai-autonomous-networks", "s": "Introduces architectural principles for integrating AI agents into IP protocol stack layers while preserving deterministic protocol behavior. Proposes agent controllers for cross-layer coordination.", "n": 4, "nn": "Novel approach to layered agentic augmentation of existing protocols", "m": 3, "mn": "12-page research document with solid architectural thinking", "o": 2, "on": "Unique approach to protocol stack integration", "mo": 4, "mon": "Strong conceptual foundation for research community discussion", "r": 5, "rn": "Highly relevant as foundational architecture for agentic networking", "c": ["Autonomous netops", "A2A protocols", "Policy/governance"]}


draft_name: draft-cowles-volt
prompt_hash: 8f0ccb0f594b4946
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:11.377577+00:00
response_json:
  {"name": "draft-cowles-volt", "s": "Defines tamper-evident execution trace format for AI agent workflows using hash chains and cryptographic integrity. Provides privacy-first audit trails for agent operations.", "n": 5, "nn": "Highly novel approach to AI agent auditability and transparency", "m": 5, "mn": "Comprehensive 40-page specification with detailed technical design", "o": 1, "on": "Unique focus on verifiable agent operation logging", "mo": 4, "mon": "Addresses critical need for AI transparency and accountability", "r": 5, "rn": "Extremely relevant for trustworthy AI agent deployments", "c": ["AI safety/alignment", "Data formats/interop", "Policy/governance", "Agent identity/auth"]}


draft_name: draft-du-catalist-routing-considerations
prompt_hash: 8a09e50a7129f105
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:29.087557+00:00
response_json:
  {"name": "draft-du-catalist-routing-considerations", "s": "Proposes routing considerations for AI agent-to-agent communication in overlay networks. Focuses on cross-domain scenarios where agents with different skills need to interconnect.", "n": 4, "nn": "Novel focus on agent-specific routing requirements in overlay networks", "m": 2, "mn": "Brief 8-page document lacks detailed technical specifications", "o": 2, "on": "Some overlap with other agentic network drafts but unique routing focus", "mo": 3, "mon": "Part of emerging agentic networking trend but limited scope", "r": 4, "rn": "Highly relevant as AI agents proliferate and need interconnection", "c": ["A2A protocols", "ML traffic mgmt", "Agent discovery/reg"]}


draft_name: draft-yc-ipv6-for-ioa
prompt_hash: 5cacf971325cc98d
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:29.109301+00:00
response_json:
  {"name": "draft-yc-ipv6-for-ioa", "s": "Analyzes IPv6 capabilities for supporting Internet of Agents (IoA) infrastructure. Explores how IPv6's address space and features can enable billions of intelligent agents.", "n": 3, "nn": "Applies existing IPv6 to new IoA domain with some novel requirements", "m": 2, "mn": "7-page analysis document without concrete protocol extensions", "o": 3, "on": "Overlaps conceptually with other IoA drafts but IPv6-specific angle", "mo": 3, "mon": "Builds on established IPv6 foundation for emerging IoA applications", "r": 4, "rn": "Very relevant for scaling agent communications to massive deployments", "c": ["Agent identity/auth", "Agent discovery/reg", "Data formats/interop"]}


draft_name: draft-chen-nmrg-semantic-inference-routing
prompt_hash: 8a67dcc61fbecffb
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:29.119816+00:00
response_json:
  {"name": "draft-chen-nmrg-semantic-inference-routing", "s": "Defines SIRP protocol for content-aware routing of AI inference requests. Enables routing decisions based on semantic analysis rather than just client metadata.", "n": 4, "nn": "Novel semantic content analysis approach for inference routing", "m": 3, "mn": "12-page specification with concrete protocol framework", "o": 2, "on": "Unique semantic routing approach with minimal overlap", "mo": 4, "mon": "Addresses critical inference routing challenges with technical depth", "r": 5, "rn": "Extremely relevant for optimizing distributed AI inference systems", "c": ["Model serving/inference", "ML traffic mgmt", "Autonomous netops"]}


draft_name: draft-chen-nmrg-multi-provider-inference-api
prompt_hash: 269634d5e9b30cf8
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:29.141290+00:00
response_json:
  {"name": "draft-chen-nmrg-multi-provider-inference-api", "s": "Specifies extensions for multi-provider AI inference using OpenAI API as reference standard. Enables provider diversity, load balancing, and failover while maintaining backward compatibility.", "n": 3, "nn": "Extends existing OpenAI API standard for multi-provider scenarios", "m": 5, "mn": "Comprehensive 44-page specification with detailed technical content", "o": 3, "on": "Some overlap with inference serving concepts but unique multi-provider focus", "mo": 4, "mon": "Addresses practical multi-provider challenges with mature specification", "r": 5, "rn": "Highly relevant for preventing vendor lock-in in AI inference deployments", "c": ["Model serving/inference", "Data formats/interop", "Policy/governance"]}


draft_name: draft-calabria-bmwg-ai-fabric-inference-bench
prompt_hash: 8ff660c77d7d63d8
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:29.155925+00:00
response_json:
  {"name": "draft-calabria-bmwg-ai-fabric-inference-bench", "s": "Defines benchmarking methodology for AI inference network fabrics. Establishes KPIs and test procedures for evaluating fabric performance under realistic inference workloads.", "n": 4, "nn": "First comprehensive benchmarking framework for AI inference fabrics", "m": 5, "mn": "Extensive 40-page methodology with detailed test procedures and KPIs", "o": 1, "on": "Unique benchmarking focus with minimal overlap to other drafts", "mo": 4, "mon": "Addresses critical need for standardized AI fabric performance evaluation", "r": 5, "rn": "Essential for comparing and optimizing AI inference infrastructure", "c": ["ML traffic mgmt", "Model serving/inference", "Other AI/agent"]}


draft_name: draft-tsyrulnikov-rats-attested-inference-receipt
prompt_hash: 5eda7ff3265fa395
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:48.591674+00:00
response_json:
  {"name": "draft-tsyrulnikov-rats-attested-inference-receipt", "s": "Defines Attested Inference Receipt (AIR) using COSE/CWT to create verifiable receipts for confidential AI inference events in TEEs. Binds model identity, input/output hashes, and platform attestation into signed artifacts for audit and compliance.", "n": 4, "nn": "Novel application of existing COSE/CWT standards to AI inference attestation with specific TEE platform support", "m": 4, "mn": "Well-structured technical specification with clear scope and concrete platform implementations", "o": 2, "on": "Some overlap with general attestation work but specific to AI inference use cases", "mo": 3, "mon": "Addresses growing need for AI transparency but limited to specific TEE environments", "r": 4, "rn": "Highly relevant for confidential AI and regulatory compliance requirements", "c": ["Model serving/inference", "Agent identity/auth", "Data formats/interop"]}


draft_name: draft-jimenez-tbd-robotstxt-update
prompt_hash: 07ac74e794df5534
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:48.616515+00:00
response_json:
  {"name": "draft-jimenez-tbd-robotstxt-update", "s": "Proposes updates to robots.txt standard to handle AI-specific crawlers with new syntax for user-agent identification. Aims to distinguish between training and inference activities for better web content access management.", "n": 3, "nn": "Evolutionary update to existing standard addressing new AI crawler use cases", "m": 2, "mn": "Brief document with limited technical depth, appears early stage", "o": 1, "on": "Unique focus on robots.txt for AI applications", "mo": 4, "mon": "High relevance due to widespread AI training concerns and web scraping issues", "r": 4, "rn": "Very relevant to current debates about AI training data and web content rights", "c": ["Policy/governance", "Agent discovery/reg"]}


draft_name: draft-improving-data-quality-tags
prompt_hash: 72a19ad2ebf974e3
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:48.628444+00:00
response_json:
  {"name": "draft-improving-data-quality-tags", "s": "Proposes special text tags to enhance data quality and improve conversational AI model understanding. Tags provide additional context and structure during training and inference for more accurate responses.", "n": 2, "nn": "Straightforward application of markup concepts to AI training data", "m": 2, "mn": "Very brief document lacking detailed technical specification", "o": 3, "on": "Some similarity to existing markup and metadata approaches", "mo": 2, "mon": "Limited scope and unclear adoption path", "r": 3, "rn": "Relevant to AI training quality but approach may be too simplistic", "c": ["Data formats/interop", "AI safety/alignment"]}


draft_name: draft-tjw-dbound2-problem-statement
prompt_hash: f3611236841d5401
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:48.638341+00:00
response_json:
  {"name": "draft-tjw-dbound2-problem-statement", "s": "Outlines problems with determining organizational boundaries in DNS when clients make administrative relationship inferences. Identifies issues with current mitigation strategies for domain boundary determination.", "n": 2, "nn": "Problem statement for existing DNS organizational boundary issues", "m": 3, "mn": "Good problem identification but limited to problem statement phase", "o": 4, "on": "Overlaps with existing DNS security and organizational identity work", "mo": 2, "mon": "Long-standing problem with unclear urgency for AI-specific solutions", "r": 2, "rn": "Peripherally relevant to AI agents needing to understand domain relationships", "c": ["Agent identity/auth", "Policy/governance"]}


draft_name: draft-yao-tsvwg-cco-requirement-and-analysis
prompt_hash: 3335c3687ce77ca7
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:41:48.650241+00:00
response_json:
  {"name": "draft-yao-tsvwg-cco-requirement-and-analysis", "s": "Analyzes collective communication optimizations for AI training and inference clusters built on RDMA. Examines network-assisted collective acceleration approaches and identifies gaps with current IETF standards like iWARP.", "n": 4, "nn": "Detailed analysis of network optimization needs specific to AI workloads", "m": 4, "mn": "Comprehensive analysis with clear requirements and technical depth", "o": 3, "on": "Some overlap with HPC networking but specific AI workload focus", "mo": 4, "mon": "Strong momentum due to massive AI infrastructure investments", "r": 5, "rn": "Extremely relevant as AI model sizes and training requirements continue growing", "c": ["ML traffic mgmt", "Model serving/inference"]}


draft_name: draft-hong-nmrg-ai-deploy
prompt_hash: b6dc6138061a5e6a
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:09.178440+00:00
response_json:
  {"name": "draft-hong-nmrg-ai-deploy", "s": "Describes network and system configurations for distributed AI inference services, covering deployment considerations for edge and cloud environments. Includes use cases like self-driving vehicles and network digital twins.", "n": 2, "nn": "Basic coverage of distributed AI deployment, but lacks novel technical contributions or specific protocols", "m": 2, "mn": "Early draft with grammar issues and incomplete technical details", "o": 4, "on": "Heavily overlaps with draft-irtf-nmrg-ai-deploy which appears to be an updated version", "mo": 2, "mon": "Superseded by the IRTF version, limited independent momentum", "r": 3, "rn": "Addresses relevant distributed AI deployment challenges but at a high level", "c": ["Model serving/inference", "ML traffic mgmt"]}


draft_name: draft-ai-traffic
prompt_hash: 35247f358d48d195
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:09.200792+00:00
response_json:
  {"name": "draft-ai-traffic", "s": "Problem statement for handling AI/LLM traffic between datacenters and edge locations. Focuses on understanding network characteristics of distributed AI training and inference workloads.", "n": 3, "nn": "Good identification of federated AI networking challenges, though problem statement only", "m": 2, "mn": "Problem statement level, lacks concrete solutions or protocols", "o": 5, "on": "Identical content to draft-aft-ai-traffic, appears to be duplicate or renamed draft", "mo": 1, "mon": "Old version from 2024, likely superseded by the aft version", "r": 4, "rn": "Highly relevant to current federated AI trends and inter-DC traffic management needs", "c": ["ML traffic mgmt", "Model serving/inference"]}


draft_name: draft-aft-ai-traffic
prompt_hash: a47d7c9d84492207
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:09.212199+00:00
response_json:
  {"name": "draft-aft-ai-traffic", "s": "Problem statement addressing network traffic challenges for federated LLM training and inference across datacenters. Emphasizes understanding AI workload characteristics for distributed operations.", "n": 3, "nn": "Solid problem identification for federated AI, but remains at problem statement level", "m": 3, "mn": "More recent version, better positioned but still needs solution development", "o": 5, "on": "Identical abstract to draft-ai-traffic, appears to be same work under different name", "mo": 3, "mon": "More recent version suggests continued interest, but needs solution development", "r": 4, "rn": "Addresses critical federated AI networking challenges relevant to industry needs", "c": ["ML traffic mgmt", "Model serving/inference"]}


draft_name: draft-irtf-nmrg-ai-deploy
prompt_hash: fd463ff23ba4fcd3
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:09.223422+00:00
response_json:
  {"name": "draft-irtf-nmrg-ai-deploy", "s": "Outlines network and system configuration for distributed AI inference services across edge and cloud environments. Covers deployment considerations and use cases for network-based AI services.", "n": 2, "nn": "Incremental improvement over earlier version but still lacks specific technical innovations", "m": 3, "mn": "Better written than earlier version, under IRTF umbrella suggests more formal review", "o": 4, "on": "Very similar to draft-hong-nmrg-ai-deploy, appears to be refined version", "mo": 3, "mon": "IRTF adoption suggests institutional support and continued development", "r": 3, "rn": "Relevant distributed AI deployment guidance, though at high architectural level", "c": ["Model serving/inference", "ML traffic mgmt"]}


draft_name: draft-dunbar-neotec-ac-te-applicability
prompt_hash: ea4897084996d4b4
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:09.234988+00:00
response_json:
  {"name": "draft-dunbar-neotec-ac-te-applicability", "s": "Applies existing IETF YANG models for Attachment Circuits and Traffic Engineering to dynamic AI model placement at edge sites. Evaluates model applicability for AI inference use cases with specific network performance requirements.", "n": 4, "nn": "Novel application of existing YANG models to AI placement, practical approach to leveraging current standards", "m": 4, "mn": "Well-developed technical approach with concrete YANG model applications and gap analysis", "o": 1, "on": "Unique focus on applying existing YANG models to AI placement scenarios", "mo": 3, "mon": "Specific technical approach with practical implementation path", "r": 4, "rn": "Highly relevant for operators needing to integrate AI services with existing network management", "c": ["Model serving/inference", "Data formats/interop", "ML traffic mgmt"]}


draft_name: draft-zhu-anima-service-intent
prompt_hash: 884ed2a148a8528f
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:29.763928+00:00
response_json:
  {"name": "draft-zhu-anima-service-intent", "s": "Defines a structured semantic model for expressing service-level objectives and constraints across network, compute, and storage resources in autonomic networks. Extends ANIMA Intent to support emerging AI inference services with proper identification, scope, versioning, and lifecycle management.", "n": 3, "nn": "Builds on existing ANIMA Intent but adds service-level abstractions for multi-resource scenarios", "m": 3, "mn": "Provides semantic model and format specification but likely needs implementation validation", "o": 2, "on": "Related to ANIMA work but focuses on service-level rather than connection-centric intent", "mo": 3, "mon": "Addresses growing need for AI service orchestration in autonomic networks", "r": 4, "rn": "Highly relevant for AI service deployment and autonomous network management", "c": ["Autonomous netops", "Model serving/inference", "Policy/governance"]}


draft_name: draft-zhang-rtgwg-multicast-requirements-gaps-aidc
prompt_hash: a180bad8041fd90b
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:29.786893+00:00
response_json:
  {"name": "draft-zhang-rtgwg-multicast-requirements-gaps-aidc", "s": "Identifies requirements for multicast technology in AI Data Centers to improve efficiency of point-to-multipoint data transmission during model training and inference. Analyzes gaps between current multicast capabilities and AIDC needs.", "n": 4, "nn": "First systematic analysis of multicast requirements specifically for AI datacenter workloads", "m": 3, "mn": "Requirements analysis is solid but gaps analysis needs validation against real deployments", "o": 1, "on": "Unique focus on multicast for AI datacenters", "mo": 4, "mon": "Strong relevance to scaling AI training and inference infrastructure", "r": 4, "rn": "Critical for efficient AI model training and distributed inference at scale", "c": ["ML traffic mgmt", "Model serving/inference"]}


draft_name: draft-hu-neotec-usecases-notc
prompt_hash: 9becba4c65f203fc
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:29.797097+00:00
response_json:
  {"name": "draft-hu-neotec-usecases-notc", "s": "Presents network operations use cases for telco cloud orchestration including AI-based video recognition and dynamic bandwidth transport. Demonstrates elastic provisioning, failover mechanisms, and cross-domain resource scheduling for telecom cloud environments.", "n": 2, "nn": "Applies existing concepts to telco cloud scenarios rather than introducing new technical approaches", "m": 2, "mn": "Use case descriptions lack technical depth and standardization specifics", "o": 3, "on": "Overlaps with general cloud orchestration and network slicing work", "mo": 3, "mon": "Relevant to telco AI adoption but limited technical innovation", "r": 3, "rn": "Moderately relevant for telco AI deployments but lacks technical depth", "c": ["Autonomous netops", "Model serving/inference", "Other AI/agent"]}


draft_name: draft-williams-netmod-lm-hierarchy-topology
prompt_hash: 0c460f4ea36e1da7
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:29.807687+00:00
response_json:
  {"name": "draft-williams-netmod-lm-hierarchy-topology", "s": "Defines YANG data model for hierarchical language model coordination across tiny, small, and large LMs in distributed inference scenarios. Includes secure messaging, request escalation, and pluggable trust models for edge-to-cloud AI deployments.", "n": 5, "nn": "Novel hierarchical LM coordination architecture with comprehensive security and trust mechanisms", "m": 4, "mn": "Well-structured YANG model with clear architecture but needs interoperability testing", "o": 1, "on": "Unique approach to hierarchical LM coordination with formal data modeling", "mo": 4, "mon": "Addresses critical need for distributed AI inference coordination", "r": 5, "rn": "Highly relevant for edge AI, federated inference, and multi-tier AI system coordination", "c": ["A2A protocols", "Agent identity/auth", "Data formats/interop", "Model serving/inference"]}


draft_name: draft-silver-aipref-vocab-substitutive
prompt_hash: b3964762e6ce5bae
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:29.818055+00:00
response_json:
  {"name": "draft-silver-aipref-vocab-substitutive", "s": "Proposes vocabulary for expressing preferences about AI substitutive usage of digital assets, focusing on inference-time uses that create outputs substituting for original content. Nests within broader automated processing preference framework.", "n": 3, "nn": "Specific focus on substitutive AI usage is novel within preference expression frameworks", "m": 2, "mn": "Early stage vocabulary proposal that needs broader community input and refinement", "o": 2, "on": "Related to general AI preference frameworks but focuses on specific substitutive use case", "mo": 3, "mon": "Growing importance of AI usage preferences but early adoption phase", "r": 4, "rn": "High relevance for content protection and AI governance discussions", "c": ["Policy/governance", "Data formats/interop"]}


draft_name: draft-wang-cats-innetwork-infer
prompt_hash: 5d0754c4ed6d0ebd
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:47.663048+00:00
response_json:
  {"name": "draft-wang-cats-innetwork-infer", "s": "Proposes a framework for decentralized LLM inference across untrusted participants using layer-aware activation transport. Focuses on architectural design for distributed inference with explicit deadlines and security mechanisms.", "n": 4, "nn": "Novel approach to decentralized LLM inference with layer-aware transport", "m": 2, "mn": "Architectural framework only, lacks concrete protocols and wire formats", "o": 3, "on": "Overlaps with other distributed inference drafts but unique decentralized approach", "mo": 3, "mon": "Addresses important scalability concerns but implementation complexity may limit adoption", "r": 4, "rn": "Highly relevant to distributed AI infrastructure needs", "c": ["Model serving/inference", "A2A protocols", "ML traffic mgmt"]}


draft_name: draft-reilly-sentinel-protocol
prompt_hash: a80b23c81d010a38
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:47.673561+00:00
response_json:
  {"name": "draft-reilly-sentinel-protocol", "s": "Defines blockchain-anchored integrity protocol for AI lifecycle provenance using Sentinel Evidence Packages. Provides tamper-evident audit trails for datasets, training, and inference.", "n": 4, "nn": "Creative combination of blockchain timestamping with AI provenance tracking", "m": 3, "mn": "Well-defined protocol structure but needs implementation validation", "o": 2, "on": "Unique focus on blockchain-anchored AI provenance", "mo": 3, "mon": "Addresses regulatory compliance needs but blockchain dependency may limit adoption", "r": 4, "rn": "Very relevant for regulated AI deployments and safety-critical applications", "c": ["AI safety/alignment", "Data formats/interop", "Policy/governance"]}


draft_name: draft-dunbar-onions-ac-te-applicability
prompt_hash: f2dbd762e0f16bb8
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:47.682843+00:00
response_json:
  {"name": "draft-dunbar-onions-ac-te-applicability", "s": "Explores applying existing YANG data models for attachment circuits and traffic engineering to edge AI placement. Evaluates model applicability for dynamic AI inference location selection.", "n": 2, "nn": "Application of existing models rather than new protocol development", "m": 3, "mn": "Practical exercise with concrete use case but limited to existing tools", "o": 2, "on": "Unique application of YANG models to AI edge placement", "mo": 2, "mon": "Limited scope as applicability study rather than new solution", "r": 3, "rn": "Moderately relevant for edge AI deployment optimization", "c": ["ML traffic mgmt", "Model serving/inference", "Autonomous netops"]}


draft_name: draft-shi-moq-kvcache
prompt_hash: aa4f8c4e81555288
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:47.693830+00:00
response_json:
  {"name": "draft-shi-moq-kvcache", "s": "Specifies transmission of LLM KVCache over MoQT for efficient reuse and bandwidth savings. Leverages publish/subscribe transport for local caching of inference state.", "n": 3, "nn": "Practical application of MoQT to specific LLM caching needs", "m": 2, "mn": "Short specification needing more detailed protocol definition", "o": 4, "on": "Significant overlap with general MoQT and caching mechanisms", "mo": 3, "mon": "Addresses clear efficiency need but limited scope", "r": 4, "rn": "Highly relevant for LLM inference optimization", "c": ["ML traffic mgmt", "Model serving/inference", "Data formats/interop"]}


draft_name: draft-song-rtgwg-din-usecases-requirements
prompt_hash: 0f04e763cab7a9ec
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:42:47.705111+00:00
response_json:
  {"name": "draft-song-rtgwg-din-usecases-requirements", "s": "Defines problem statement and requirements for Distributed Inference Networks addressing scalability and latency challenges. Focuses on edge-cloud collaboration for AI inference services.", "n": 2, "nn": "Problem statement document rather than novel technical solution", "m": 2, "mn": "Early stage requirements document without concrete solutions", "o": 4, "on": "Substantial overlap with other distributed inference problem statements", "mo": 3, "mon": "Good problem articulation but needs follow-up solution drafts", "r": 4, "rn": "Highly relevant for distributed AI infrastructure planning", "c": ["Model serving/inference", "ML traffic mgmt", "Autonomous netops"]}


draft_name: draft-tan-ccamp-uonaco-problem-statement
prompt_hash: 113e23f309c66579
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:09.168511+00:00
response_json:
  {"name": "draft-tan-ccamp-uonaco-problem-statement", "s": "Defines requirements for unified orchestration between optical networks and AI computing to enable coordinated resource provisioning. Addresses the problem of isolated control planes preventing optimal AI workload performance across distributed data centers.", "n": 4, "nn": "Novel approach to joint optical-compute orchestration for AI workloads with bidirectional awareness", "m": 2, "mn": "Problem statement stage with basic requirements definition, lacks detailed protocol specifications", "o": 2, "on": "Some overlap with general network-compute coordination but specific to optical networks and AI", "mo": 3, "mon": "Addresses growing need for AI infrastructure coordination but early stage draft", "r": 4, "rn": "Highly relevant to emerging AI infrastructure needs and distributed training requirements", "c": ["ML traffic mgmt", "Autonomous netops", "Policy/governance"]}


draft_name: draft-ramadan-mboned-sonar
prompt_hash: 8f9be366ff0fc8ce
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:09.191779+00:00
response_json:
  {"name": "draft-ramadan-mboned-sonar", "s": "Specifies a protocol for verifiable multicast delivery using cryptoeconomic accountability and statistical sampling. Combines IP multicast efficiency with blockchain-based attestation and VRF sampling for coverage verification.", "n": 5, "nn": "Highly novel combination of multicast, cryptoeconomics, zkSNARKs, and statistical verification", "m": 4, "mn": "Detailed protocol specification with concrete parameters and implementation considerations", "o": 1, "on": "Unique approach combining multicast with cryptoeconomic verification mechanisms", "mo": 2, "mon": "Complex protocol with blockchain dependencies may limit adoption momentum", "r": 3, "rn": "Relevant for verifiable content distribution but narrow use case scope", "c": ["A2A protocols", "Agent identity/auth", "Data formats/interop"]}


draft_name: draft-xu-rtgwg-fare-in-sun
prompt_hash: 2ecf7bbfbb21c7dc
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:09.206949+00:00
response_json:
  {"name": "draft-xu-rtgwg-fare-in-sun", "s": "Extends WECMP load balancing for AI scale-up networks supporting MoE architectures. Adapts existing scale-out network techniques for high-throughput, low-latency GPU interconnection.", "n": 2, "nn": "Incremental extension of existing WECMP to different network topology", "m": 2, "mn": "Brief document with basic concept description, lacks detailed protocol mechanisms", "o": 3, "on": "Builds heavily on existing WECMP mechanisms with AI-specific application", "mo": 3, "mon": "Addresses practical AI infrastructure needs but limited technical depth", "r": 4, "rn": "Very relevant to current AI training infrastructure requirements for MoE models", "c": ["ML traffic mgmt", "Data formats/interop"]}


draft_name: draft-jain-lisp-network-ai-infra
prompt_hash: 065ba7b248eec478
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:09.217368+00:00
response_json:
  {"name": "draft-jain-lisp-network-ai-infra", "s": "Applies LISP control plane mechanisms to AI infrastructure supporting scale-up, scale-out, and scale-across deployments. Leverages existing LISP features for unified control plane across heterogeneous accelerator fabrics.", "n": 2, "nn": "Application of existing LISP protocol to AI infrastructure use case", "m": 3, "mn": "Comprehensive application document with detailed LISP mechanism usage", "o": 4, "on": "Heavy reliance on existing LISP specifications with AI-specific deployment patterns", "mo": 3, "mon": "Builds on established LISP foundation but AI infrastructure application is emerging", "r": 4, "rn": "Highly relevant for AI infrastructure needing unified control plane across diverse fabrics", "c": ["ML traffic mgmt", "Autonomous netops", "Agent discovery/reg"]}


draft_name: draft-dunbar-neotec-ac-pe2pe-ucmp-applicability
prompt_hash: 100b598cdde2c31c
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:09.228683+00:00
response_json:
  {"name": "draft-dunbar-neotec-ac-pe2pe-ucmp-applicability", "s": "Evaluates existing YANG data models for dynamic UCMP policy enforcement across edge cloud sites. Identifies gaps in current IETF specifications for time-scoped, cloud-initiated network policies.", "n": 1, "nn": "Applicability study of existing models rather than novel protocol development", "m": 3, "mn": "Thorough analysis document with practical evaluation of existing specifications", "o": 4, "on": "Heavily references and applies existing YANG models with gap analysis", "mo": 2, "mon": "Incremental analysis work with limited new technical contributions", "r": 3, "rn": "Relevant for understanding current model limitations in dynamic policy scenarios", "c": ["ML traffic mgmt", "Policy/governance", "Data formats/interop"]}


draft_name: draft-dunbar-onsen-ac-pe2pe-ucmp-applicability
prompt_hash: f88cf995a0a446ab
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:28.948842+00:00
response_json:
  {"name": "draft-dunbar-onsen-ac-pe2pe-ucmp-applicability", "s": "Applies existing IETF YANG models to dynamic UCMP policy enforcement for AI inference traffic between distributed edge data centers. Identifies gaps in current models for cloud-initiated, time-bounded network policy coordination.", "n": 2, "nn": "Limited novelty - primarily applies existing YANG models to new use case", "m": 3, "mn": "Well-structured analysis but relies heavily on existing specifications", "o": 3, "on": "Moderate overlap with general YANG model applicability studies", "mo": 2, "mon": "Niche application area with limited immediate adoption potential", "r": 3, "rn": "Relevant for AI infrastructure networking but very specialized scope", "c": ["ML traffic mgmt", "Model serving/inference"]}


draft_name: draft-dunbar-onsen-ac-te-applicability
prompt_hash: 1d3d97da8cd86835
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:28.972683+00:00
response_json:
  {"name": "draft-dunbar-onsen-ac-te-applicability", "s": "Explores application of IETF AC and TE YANG models for dynamic AI model placement at edge cloud sites. Focuses on network performance-based optimization for real-time AI inference.", "n": 2, "nn": "Similar approach to companion draft - applying existing models to AI use cases", "m": 3, "mn": "Comprehensive analysis but primarily an applicability study", "o": 4, "on": "Significant overlap with companion UCMP draft and general TE work", "mo": 2, "mon": "Limited broader applicability beyond specific edge AI scenarios", "r": 3, "rn": "Addresses relevant edge AI deployment challenges but narrow focus", "c": ["ML traffic mgmt", "Model serving/inference"]}


draft_name: draft-calabria-bmwg-ai-fabric-terminology
prompt_hash: b16e62584f840641
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:28.984157+00:00
response_json:
  {"name": "draft-calabria-bmwg-ai-fabric-terminology", "s": "Defines comprehensive benchmarking terminology for AI network fabrics including collective communication primitives and RDMA transport mechanisms. Establishes vendor-neutral vocabulary for AI networking performance evaluation.", "n": 4, "nn": "Significant contribution to standardizing AI networking terminology", "m": 4, "mn": "Well-developed terminology framework with clear scope and references", "o": 2, "on": "Extends existing benchmarking RFCs but focuses on new AI domain", "mo": 4, "mon": "Strong foundation work that enables broader AI networking standardization", "r": 5, "rn": "Highly relevant as foundational work for AI infrastructure standardization", "c": ["ML traffic mgmt", "Data formats/interop"]}


draft_name: draft-ruan-spring-priority-flow-control-sid
prompt_hash: da19a1e78f7faa88
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:28.994577+00:00
response_json:
  {"name": "draft-ruan-spring-priority-flow-control-sid", "s": "Extends SRv6 with flow control capabilities for WAN environments supporting RDMA-based AI workloads. Enables congestion notification and response for distributed AI training and inference.", "n": 3, "nn": "Novel application of SRv6 to AI traffic flow control in WAN scenarios", "m": 2, "mn": "Technical approach appears sound but document seems incomplete", "o": 2, "on": "Builds on SRv6 but addresses distinct flow control requirements", "mo": 3, "mon": "Growing interest in AI traffic management but early stage work", "r": 4, "rn": "Addresses important WAN flow control needs for distributed AI", "c": ["ML traffic mgmt", "A2A protocols"]}


draft_name: draft-li-spring-rdma-multicast-over-srv6
prompt_hash: b251c2d31baab88b
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:29.003900+00:00
response_json:
  {"name": "draft-li-spring-rdma-multicast-over-srv6", "s": "Specifies SRv6 extensions for RDMA multicast delivery with new End.MT behavior and ACK/NACK aggregation procedures. Targets AI training parameter distribution and distributed storage scenarios.", "n": 4, "nn": "Novel combination of RDMA multicast semantics with SRv6 segment routing", "m": 4, "mn": "Detailed technical specification with clear protocol extensions", "o": 2, "on": "Unique approach to RDMA multicast - limited overlap with existing work", "mo": 4, "mon": "Addresses critical scalability needs for distributed AI workloads", "r": 5, "rn": "Highly relevant for large-scale AI training and inference deployment", "c": ["ML traffic mgmt", "A2A protocols"]}


draft_name: draft-intellinode-ai-semantic-contract
prompt_hash: a1869d0ac4145585
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:52.288638+00:00
response_json:
  {"name": "draft-intellinode-ai-semantic-contract", "s": "Defines contracts allowing AI applications to communicate semantic information about tensor flows to networks for optimized scheduling. Networks commit to differentiated forwarding based on these semantics and real-time states.", "n": 4, "nn": "Novel approach to expose AI workload semantics to network layer for optimization", "m": 2, "mn": "Very brief document with limited technical detail and no protocol specifics", "o": 3, "on": "Overlaps with other IntelliNode drafts on AI-aware networking", "mo": 2, "mon": "Short document suggests early-stage development with limited backing", "r": 4, "rn": "Highly relevant to emerging AI infrastructure optimization needs", "c": ["ML traffic mgmt", "Data formats/interop"]}


draft_name: draft-li-cats-idn
prompt_hash: 82e8669a35b670b5
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:52.313266+00:00
response_json:
  {"name": "draft-li-cats-idn", "s": "Introduces Intelligence Delivery Network (IDN) framework for deploying ML models across distributed servers for latency-aware inference. Focuses on architectural framework and vocabulary without protocol details.", "n": 3, "nn": "Extends CDN concepts to AI inference but builds on established distributed computing ideas", "m": 3, "mn": "Reasonable length with architectural framework but explicitly defers protocol details", "o": 2, "on": "Some overlap with ODSI on distributed inference but different focus areas", "mo": 3, "mon": "Moderate length and framework approach suggests some development investment", "r": 5, "rn": "Addresses critical need for distributed AI inference infrastructure", "c": ["Model serving/inference", "Agent discovery/reg"]}


draft_name: draft-intellinode-cats-in-network-scheduling
prompt_hash: 40714613a92ff6f5
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:52.324038+00:00
response_json:
  {"name": "draft-intellinode-cats-in-network-scheduling", "s": "Introduces IntelliNode mechanism for AI-aware network scheduling using FPGA-enhanced switches. Creates closed-loop system for real-time tensor flow optimization and heterogeneous compute matching.", "n": 4, "nn": "Innovative integration of FPGAs in network switches for AI workload optimization", "m": 2, "mn": "Brief document with high-level architecture but limited implementation details", "o": 5, "on": "Appears to be duplicate or very similar to draft-li-cats-intellinode-network-scheduling", "mo": 2, "mon": "Short length and potential duplication suggests coordination issues", "r": 4, "rn": "Addresses important AI infrastructure optimization challenges", "c": ["ML traffic mgmt", "Autonomous netops"]}


draft_name: draft-li-cats-intellinode-network-scheduling
prompt_hash: 94e4178a2e31bc16
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:52.332821+00:00
response_json:
  {"name": "draft-li-cats-intellinode-network-scheduling", "s": "Introduces IntelliNode mechanism for AI-aware network scheduling using FPGA-enhanced switches. Creates closed-loop system for real-time tensor flow optimization and heterogeneous compute matching.", "n": 4, "nn": "Innovative integration of FPGAs in network switches for AI workload optimization", "m": 2, "mn": "Brief document with high-level architecture but limited implementation details", "o": 5, "on": "Appears to be duplicate or very similar to draft-intellinode-cats-in-network-scheduling", "mo": 1, "mon": "Duplicate submission suggests poor coordination and low momentum", "r": 4, "rn": "Addresses important AI infrastructure optimization challenges", "c": ["ML traffic mgmt", "Autonomous netops"]}


draft_name: draft-wang-cats-odsi
prompt_hash: 9c018b643ae056de
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:43:52.341007+00:00
response_json:
  {"name": "draft-wang-cats-odsi", "s": "Specifies framework for decentralized LLM inference across untrusted participants with layer-aware execution. Addresses openness, scalability, and security challenges in distributed AI inference.", "n": 5, "nn": "Novel approach to decentralized, trustless LLM inference with layer-aware coordination", "m": 4, "mn": "Substantial document with comprehensive framework though protocol details deferred", "o": 2, "on": "Some conceptual overlap with IDN but focuses on decentralization and security", "mo": 4, "mon": "Lengthy detailed document suggests significant development effort and commitment", "r": 5, "rn": "Addresses critical challenges in scalable, open AI infrastructure", "c": ["Model serving/inference", "Agent identity/auth", "Policy/governance"]}


draft_name: draft-li-cats-aisemantic-contract
prompt_hash: d8f29e6cf9ec40b0
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:14.208975+00:00
response_json:
  {"name": "draft-li-cats-aisemantic-contract", "s": "Defines a contract mechanism allowing AI applications to communicate semantic information about their traffic to networks. Networks use this information to provide differentiated resource allocation and forwarding for AI workloads.", "n": 4, "nn": "Novel approach to expose AI traffic semantics to network layer for optimized handling", "m": 2, "mn": "Early stage work with basic contract definition, lacks detailed implementation specifics", "o": 2, "on": "Some overlap with general traffic engineering but unique AI semantic focus", "mo": 3, "mon": "Growing interest in AI-aware networking but still niche area", "r": 4, "rn": "Highly relevant as AI workloads become dominant in data centers", "c": ["ML traffic mgmt", "Data formats/interop"]}


draft_name: draft-li-individual-inip
prompt_hash: d7cfabf807d4e8b7
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:14.228351+00:00
response_json:
  {"name": "draft-li-individual-inip", "s": "Specifies a protocol for performing lightweight ML inference directly in network devices like switches and SmartNICs. Uses centralized control plane for model management and distributed data plane for inference execution.", "n": 4, "nn": "Novel integration of inference capabilities into network data plane devices", "m": 3, "mn": "Detailed protocol specification with packet formats and architecture, but implementation complexity unclear", "o": 1, "on": "Unique approach to in-network computing for inference", "mo": 3, "mon": "Edge computing trend supports concept but network device inference is still emerging", "r": 4, "rn": "Very relevant for reducing latency and improving efficiency in AI applications", "c": ["Model serving/inference", "A2A protocols"]}


draft_name: draft-xu-sidrops-asrank-vulnerabilities
prompt_hash: 6a73c8f80ca3b369
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:14.238890+00:00
response_json:
  {"name": "draft-xu-sidrops-asrank-vulnerabilities", "s": "Analyzes security vulnerabilities in the ASRank algorithm used for inferring AS business relationships from BGP data. Identifies how adversarial manipulation could affect inference results.", "n": 3, "nn": "Important security analysis of widely-used BGP analysis tool, though builds on existing ASRank work", "m": 3, "mn": "Solid analysis with concrete examples, but primarily analytical rather than proposing solutions", "o": 2, "on": "Related to BGP security research but specific focus on ASRank vulnerabilities is unique", "mo": 3, "mon": "BGP security remains important but ASRank-specific work has limited audience", "r": 3, "rn": "Relevant for network security and BGP operations, though somewhat specialized", "c": ["AI safety/alignment", "Policy/governance"]}


draft_name: draft-cgfabk-nmrg-ibn-generative-ai
prompt_hash: 3e66f73c9d316205
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:14.249067+00:00
response_json:
  {"name": "draft-cgfabk-nmrg-ibn-generative-ai", "s": "Describes methods for specializing AI models to create targeted generative models for Intent-Based Networking. Focuses on making IBN systems more scalable and efficient through AI techniques.", "n": 3, "nn": "Applies generative AI to IBN, combining two established areas in new way", "m": 2, "mn": "Conceptual framework provided but lacks detailed technical specifications", "o": 3, "on": "Overlaps with existing IBN and AI model work but specific combination is less explored", "mo": 4, "mon": "High interest in both generative AI and network automation creates good momentum", "r": 4, "rn": "Very relevant as networks seek more intelligent automation capabilities", "c": ["Autonomous netops", "Model serving/inference"]}


draft_name: draft-song-tsvwg-camp
prompt_hash: 43dd62d91b14874a
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:14.258087+00:00
response_json:
  {"name": "draft-song-tsvwg-camp", "s": "Proposes CAMP, a multipath transport protocol for interactive multimodal LLM systems that maintains consistency across different modalities. Builds on MPQUIC with specialized scheduling for audio, video, and text streams.", "n": 4, "nn": "First work addressing multipath consistency for multimodal LLM applications", "m": 4, "mn": "Comprehensive technical specification with detailed protocol design and mechanisms", "o": 2, "on": "Builds on MPQUIC but addresses unique multimodal consistency challenges", "mo": 4, "mon": "High momentum due to growing interactive LLM applications and multimodal AI systems", "r": 5, "rn": "Extremely relevant for emerging interactive AI applications requiring real-time multimodal delivery", "c": ["A2A protocols", "Human-agent interaction", "ML traffic mgmt"]}


draft_name: draft-li-iotops-intelligent-security
prompt_hash: 447e53b5152762e4
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:34.154726+00:00
response_json:
  {"name": "draft-li-iotops-intelligent-security", "s": "Proposes an information-centered network architecture for IoT security with intelligent protection optimization across naming, data exchange, and caching layers. Aims to improve content privacy protection without additional costs.", "n": 2, "nn": "Information-centric networking for IoT security is not new, lacks specific technical innovations", "m": 1, "mn": "Very early stage with vague technical details and minimal concrete implementation guidance", "o": 4, "on": "Significant overlap with existing ICN and IoT security drafts and research", "mo": 2, "mon": "Limited adoption indicators, appears to be individual submission without broad support", "r": 3, "rn": "IoT security is relevant but approach seems disconnected from current IETF IoT work", "c": ["Autonomous netops", "Policy/governance"]}


draft_name: draft-yang-spring-sr-policy-intelligent-routing
prompt_hash: 8cb82fa07026f0f3
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:34.174059+00:00
response_json:
  {"name": "draft-yang-spring-sr-policy-intelligent-routing", "s": "Describes an intelligent routing method for SR Policy that uses network quality metrics to make routing decisions in MPLS and IPv6 environments. Extends existing SR Policy framework with quality-based path selection.", "n": 2, "nn": "Quality-based routing exists; intelligence aspect appears to be basic metrics analysis", "m": 3, "mn": "Builds on established SR Policy framework with reasonable technical depth", "o": 3, "on": "Moderate overlap with existing SR Policy and traffic engineering work", "mo": 3, "mon": "SPRING working group context provides some momentum but not clear broad support", "r": 4, "rn": "Highly relevant to current SPRING work and network optimization needs", "c": ["ML traffic mgmt", "Autonomous netops"]}


draft_name: draft-doujiali-cloudnetwork-intelligentoperation
prompt_hash: 1268421138289491
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:34.184632+00:00
response_json:
  {"name": "draft-doujiali-cloudnetwork-intelligentoperation", "s": "Proposes requirements for cloud network intelligent operation and maintenance. Very brief document outlining needs for standardized intelligent operations.", "n": 1, "nn": "Requirements-only document with no novel technical contributions", "m": 1, "mn": "Extremely immature with minimal content and no technical specifications", "o": 4, "on": "Heavy overlap with existing network management and cloud operations work", "mo": 1, "mon": "No clear working group support or adoption pathway", "r": 2, "rn": "Topic is relevant but document provides little value to IETF standardization", "c": ["Autonomous netops", "Policy/governance"]}


draft_name: draft-yang-srv6ops-intelligent-routing
prompt_hash: 6793a983e3f52523
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:34.195144+00:00
response_json:
  {"name": "draft-yang-srv6ops-intelligent-routing", "s": "Nearly identical to the SPRING SR Policy draft but focused on SRv6 operations. Describes intelligent routing method for SR Policy based on network quality metrics.", "n": 2, "nn": "Appears to be duplicate content of spring draft with minor SRv6 focus", "m": 3, "mn": "Similar technical maturity to spring version, builds on established SR foundations", "o": 5, "on": "Heavy overlap with the corresponding SPRING draft and existing SRv6 work", "mo": 2, "mon": "Potential duplication issues may harm adoption prospects", "r": 4, "rn": "SRv6 operations are highly relevant but duplication reduces value", "c": ["ML traffic mgmt", "Autonomous netops"]}


draft_name: draft-templin-intarea-aero2
prompt_hash: 0b484857d4cef755
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:34.205929+00:00
response_json:
  {"name": "draft-templin-intarea-aero2", "s": "Specifies AERO service for IP internetworking over overlay multilink networks using IPv6 ND for control messaging. Comprehensive solution for mobility, multicast, and route optimization across diverse transport scenarios.", "n": 4, "nn": "Novel integration of IPv6 ND with overlay multilink networks for comprehensive mobility solution", "m": 4, "mn": "Very detailed technical specification with 113 pages of comprehensive protocols and procedures", "o": 2, "on": "Some overlap with mobility protocols but unique approach and comprehensive scope", "mo": 3, "mon": "Substantial individual effort, unclear broader community engagement", "r": 4, "rn": "Highly relevant for mobility and multi-transport scenarios, addresses real operational needs", "c": ["A2A protocols", "Autonomous netops", "Data formats/interop"]}


draft_name: draft-khatri-sipcore-call-transfer-fail-response
prompt_hash: 4ee73f6e7631345f
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:55.531021+00:00
response_json:
  {"name": "draft-khatri-sipcore-call-transfer-fail-response", "s": "Defines a new SIP response code (497) for indicating call transfer failures with optional granular warning codes. Allows SIP entities to handle subsequent calls more intelligently based on transfer failure information.", "n": 3, "nn": "Moderate novelty - adds specific response code for call transfer scenarios, incremental improvement to SIP", "m": 4, "mn": "Well-defined scope, clear technical specification, builds on established SIP framework", "o": 2, "on": "Low overlap - addresses specific SIP response code gap not covered by existing drafts", "mo": 3, "mon": "SIP remains relevant but not cutting-edge, moderate vendor interest likely", "r": 3, "rn": "Relevant for VoIP systems and call centers, but limited to SIP-based communications", "c": ["Other AI/agent"]}


draft_name: draft-templin-intarea-aero
prompt_hash: 938cd55bb218090c
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:55.552087+00:00
response_json:
  {"name": "draft-templin-intarea-aero", "s": "Specifies Automatic Extended Route Optimization (AERO) service for IP internetworking over Overlay Multilink Network interfaces. Supports mobility management, multicast forwarding, and route optimization for air/land/sea/space applications.", "n": 4, "nn": "High novelty - comprehensive overlay networking solution with unique mobility focus", "m": 3, "mn": "Complex 120-page specification may need refinement, but technically comprehensive", "o": 3, "on": "Moderate overlap with other mobility and overlay networking solutions", "mo": 3, "mon": "Strong technical depth but niche application areas may limit adoption", "r": 4, "rn": "Highly relevant for next-gen mobility scenarios including IoT, aviation, and space networks", "c": ["Autonomous netops", "ML traffic mgmt"]}


draft_name: draft-tu-nmrg-blockchain-trusted-protocol
prompt_hash: e0ea4f23f21dc5a1
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:55.577237+00:00
response_json:
  {"name": "draft-tu-nmrg-blockchain-trusted-protocol", "s": "Defines a blockchain-based trusted protocol specifically for sixth-generation (6G) intelligent communication networks. Very brief specification with limited technical details provided.", "n": 2, "nn": "Low novelty - blockchain for networking is well-explored, 6G context adds some freshness", "m": 1, "mn": "Very low maturity - only 14 pages with minimal technical detail for such a broad topic", "o": 4, "on": "High overlap - many blockchain networking protocols exist", "mo": 2, "mon": "Blockchain networking has mixed reception, 6G timeline is distant", "r": 2, "rn": "Limited current relevance due to early 6G stage and sparse technical content", "c": ["Policy/governance", "Agent identity/auth"]}


draft_name: draft-zhao-anima-automatic-congestion-relief
prompt_hash: b03a67cabf9dc61c
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:55.589421+00:00
response_json:
  {"name": "draft-zhao-anima-automatic-congestion-relief", "s": "Introduces automatic congestion relief using intelligent traffic analysis and dynamic regulation. Focuses on real-time self-healing response to fiber failures and network congestion events.", "n": 3, "nn": "Moderate novelty - intelligent congestion management is active area, self-healing angle is useful", "m": 2, "mn": "Low maturity - only 7 pages for complex topic, lacks implementation details", "o": 3, "on": "Moderate overlap with existing traffic engineering and congestion control mechanisms", "mo": 4, "mon": "High momentum - network automation and intelligent traffic management are hot topics", "r": 4, "rn": "Highly relevant for modern network operations and autonomous systems", "c": ["Autonomous netops", "ML traffic mgmt", "AI safety/alignment"]}


draft_name: draft-xiong-rtgwg-use-cases-hp-wan
prompt_hash: 179ef065a197f64a
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:44:55.599456+00:00
response_json:
  {"name": "draft-xiong-rtgwg-use-cases-hp-wan", "s": "Describes use cases for High-performance Wide Area Networks driven by big data and intelligent computing demands. Focuses on applications requiring massive data transmission across WAN and MAN.", "n": 2, "nn": "Low novelty - high-performance networking use cases are well-documented", "m": 3, "mn": "Moderate maturity - use case document is appropriately scoped but could be more detailed", "o": 4, "on": "High overlap - many existing high-performance networking specifications and use cases", "mo": 3, "mon": "Moderate momentum - big data networking remains important but not revolutionary", "r": 3, "rn": "Relevant for data center interconnect and cloud providers, moderate broader applicability", "c": ["Data formats/interop", "ML traffic mgmt"]}


draft_name: draft-xiong-rtgwg-requirements-hp-wan
prompt_hash: 8f4a2d2f2b976b54
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:15.066246+00:00
response_json:
  {"name": "draft-xiong-rtgwg-requirements-hp-wan", "s": "Defines requirements for high-performance wide area networks to support massive data transmission between data centers. Focuses on ensuring data integrity and stable transmission for big data and intelligent computing applications.", "n": 2, "nn": "Basic requirements document for high-performance WAN, covers well-known needs", "m": 2, "mn": "Early stage requirements draft, lacks detailed technical specifications", "o": 4, "on": "Significant overlap with existing WAN optimization and data center interconnect work", "mo": 3, "mon": "Addresses current AI/big data needs but competes with established solutions", "r": 4, "rn": "Highly relevant to AI workloads requiring massive data movement between data centers", "c": ["ML traffic mgmt", "Data formats/interop"]}


draft_name: draft-chen-tsvwg-high-speed-data-express
prompt_hash: f3063f26479648e3
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:15.085566+00:00
response_json:
  {"name": "draft-chen-tsvwg-high-speed-data-express", "s": "Proposes IP-based reference architecture for high-speed data transmission using 'one low and three high' technical system. Targets AI and super-computing services requiring wide-area massive data transfer.", "n": 3, "nn": "Novel 'data express' concept with differentiated services, but builds on known IP principles", "m": 2, "mn": "Conceptual stage with reference architecture, limited implementation details", "o": 4, "on": "Overlaps with traffic engineering, QoS, and high-performance networking drafts", "mo": 3, "mon": "Good timing for AI data needs, but faces competition from existing solutions", "r": 4, "rn": "Very relevant for AI workloads needing efficient wide-area data movement", "c": ["ML traffic mgmt", "Model serving/inference"]}


draft_name: draft-mzhang-nfsv4-recursively-setting
prompt_hash: ec2c02569aaf308c
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:15.095215+00:00
response_json:
  {"name": "draft-mzhang-nfsv4-recursively-setting", "s": "Extends NFSv4 with server-side recursive attribute setting for directories and files. Applies near-data computing principles to reduce network overhead and improve efficiency.", "n": 3, "nn": "Reasonable extension to NFSv4 server-side operations, follows established patterns", "m": 3, "mn": "Well-developed proposal with clear mechanism description and rationale", "o": 2, "on": "Extends existing NFS work but addresses specific new functionality", "mo": 3, "mon": "Useful optimization but incremental improvement to existing protocol", "r": 2, "rn": "Limited AI/agent relevance, more of a general storage optimization", "c": ["Data formats/interop"]}


draft_name: draft-pan-tsvwg-pie
prompt_hash: f3d3e07b738c1b0a
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:15.105217+00:00
response_json:
  {"name": "draft-pan-tsvwg-pie", "s": "Presents PIE queue management algorithm to address bufferbloat by controlling queueing latency. Lightweight design suitable for hardware and software implementation without per-packet timestamps.", "n": 4, "nn": "Well-developed AQM algorithm with novel proportional-integral approach", "m": 5, "mn": "Mature work with simulation, theoretical analysis, and Linux testbed validation", "o": 3, "on": "Competes with other AQM schemes like CoDel but has distinct approach", "mo": 4, "mon": "Strong technical foundation and validation, addresses real network problems", "r": 3, "rn": "Relevant for AI applications requiring low latency, but general networking improvement", "c": ["ML traffic mgmt"]}


draft_name: draft-wang-data-transmission-security-irii
prompt_hash: cd3c9d8c0187b22e
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:15.113814+00:00
response_json:
  {"name": "draft-wang-data-transmission-security-irii", "s": "Examines security requirements for data transmission in Industrial Internet identity resolution systems. Focuses on protecting cross-organizational data sharing and resolution processes.", "n": 2, "nn": "Standard security analysis for industrial systems, covers expected security concerns", "m": 2, "mn": "Early analysis phase, lacks concrete security mechanisms or protocols", "o": 3, "on": "Overlaps with general industrial IoT and identity resolution security work", "mo": 2, "mon": "Addresses important area but lacks technical depth and implementation path", "r": 2, "rn": "Limited direct AI/agent relevance, more focused on industrial identity systems", "c": ["Agent identity/auth", "Policy/governance"]}


draft_name: draft-pan-aqm-pie
prompt_hash: 877ea19bacdd1a3d
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:36.028475+00:00
response_json:
  {"name": "draft-pan-aqm-pie", "s": "PIE is a lightweight queue management algorithm that addresses bufferbloat by controlling average queueing latency to reduce jitter and improve application performance. The design avoids per-packet timestamps making it suitable for both hardware and software implementation.", "n": 2, "nn": "PIE is an established AQM algorithm, this appears to be documentation of existing work", "m": 4, "mn": "Well-developed with simulation results, theoretical analysis, and Linux testbed validation", "o": 1, "on": "Focused specifically on PIE algorithm without significant overlap with other drafts", "mo": 3, "mon": "Active queue management remains relevant but PIE is already widely implemented", "r": 2, "rn": "Traditional networking problem, not directly related to AI/ML agent systems", "c": ["Other AI/agent"]}


draft_name: draft-zhao-detnet-enhanced-use-cases
prompt_hash: cb3db38dbc4b88fa
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:36.050394+00:00
response_json:
  {"name": "draft-zhao-detnet-enhanced-use-cases", "s": "Describes enhanced use cases for scaling deterministic networks beyond RFC8578, covering industrial internet, high-experience video, intelligent computing, and ISAC-enabled smart factories. Outlines common properties and network requirements for these scenarios.", "n": 3, "nn": "Extends existing DetNet work with new use cases including intelligent computing applications", "m": 3, "mn": "Comprehensive use case analysis but implementation details not yet developed", "o": 2, "on": "Builds on RFC8578 but addresses new application domains", "mo": 4, "mon": "Strong relevance to emerging industrial and AI computing requirements", "r": 3, "rn": "Relevant to AI systems requiring deterministic network behavior", "c": ["ML traffic mgmt", "Policy/governance"]}


draft_name: draft-xsaopig-nmop-service-flow-modal-mapping
prompt_hash: 83e5b72dd1872ba6
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:36.061298+00:00
response_json:
  {"name": "draft-xsaopig-nmop-service-flow-modal-mapping", "s": "Proposes a framework using ALTO protocol and SDN architecture for mapping service flow characteristics to network modal resources in multi-modal intelligent computing networks. Focuses on dynamic resource allocation and network performance optimization.", "n": 4, "nn": "Novel integration of ALTO, SDN, and multi-modal resource mapping for intelligent networks", "m": 2, "mn": "Early stage framework with limited implementation details or validation", "o": 3, "on": "Some overlap with network resource allocation approaches but unique multi-modal focus", "mo": 3, "mon": "Addresses emerging needs but unclear industry adoption", "r": 4, "rn": "Directly addresses intelligent computing network requirements and resource optimization", "c": ["ML traffic mgmt", "Autonomous netops", "Data formats/interop"]}


draft_name: draft-han-anima-ai-asa
prompt_hash: 48bf746f9a56c682
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:36.070609+00:00
response_json:
  {"name": "draft-han-anima-ai-asa", "s": "Analyzes the impact of enhancing ANIMA's Autonomic Service Agents with AI/LLM capabilities, focusing on communication protocol considerations. Explores how AI-powered ASAs could elevate network management intelligence.", "n": 4, "nn": "First to systematically consider AI/LLM integration with ANIMA ASA architecture", "m": 2, "mn": "Early analysis phase with conceptual considerations rather than concrete solutions", "o": 1, "on": "Unique focus on AI-enhanced autonomic service agents", "mo": 4, "mon": "High relevance to current AI networking trends and ANIMA evolution", "r": 5, "rn": "Directly addresses AI-powered autonomous network operations and agent communication", "c": ["A2A protocols", "Autonomous netops", "AI safety/alignment"]}


draft_name: draft-traffic-analysis-and-network-mode-mapping
prompt_hash: a90034e8dcc42e26
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:36.079707+00:00
response_json:
  {"name": "draft-traffic-analysis-and-network-mode-mapping", "s": "Presents an LLM-based framework for network traffic classification and modality mapping to improve resource allocation efficiency. Uses two-phase approach with pre-training for traffic representations and dynamic mapping for resource strategies.", "n": 4, "nn": "Novel application of LLMs to traffic analysis and multi-modal resource mapping", "m": 2, "mn": "Conceptual framework without detailed implementation or validation results", "o": 4, "on": "Significant overlap with draft-xsaopig-nmop-service-flow-modal-mapping on modal mapping concepts", "mo": 3, "mon": "Relevant to ML-driven networking but early development stage", "r": 4, "rn": "Directly applies AI/ML to traffic management and network resource optimization", "c": ["ML traffic mgmt", "Autonomous netops", "Model serving/inference"]}


draft_name: draft-liu-rtgwg-mdt-in-high-bdp
prompt_hash: 1543d674315ecd29
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:58.197317+00:00
response_json:
  {"name": "draft-liu-rtgwg-mdt-in-high-bdp", "s": "Proposes a framework for massive data transmission in high bandwidth-delay networks using nighttime idle capacity. Introduces terminal-driven parameter optimization for applications like same-day delivery services.", "n": 3, "nn": "Novel application of terminal-driven optimization for massive data transfers, though builds on existing traffic engineering concepts", "m": 2, "mn": "Early stage work with basic architecture outlined but lacks detailed technical specifications", "o": 2, "on": "Some overlap with existing traffic engineering and QoS work but focuses on specific MDT use case", "mo": 2, "mon": "Limited adoption signals, appears to be early exploratory work from single organization", "r": 3, "rn": "Addresses real need for efficient bulk data transfer but may be too application-specific for IETF", "c": ["ML traffic mgmt", "Data formats/interop"]}


draft_name: draft-templin-6man-aero3
prompt_hash: 27eb107c7ef420a1
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:58.219093+00:00
response_json:
  {"name": "draft-templin-6man-aero3", "s": "Specifies automatic extended route optimization for IP internetworking over overlay multilink networks. Targets air/land/sea/space mobile applications with IPv6 neighbor discovery control plane.", "n": 4, "nn": "Comprehensive approach to multilink overlay networking with novel OMNI interface concept", "m": 4, "mn": "Very detailed 99-page specification suggesting significant development effort and maturity", "o": 3, "on": "Overlaps with existing mobility and overlay networking solutions but offers integrated approach", "mo": 2, "mon": "Long-running work by established author but limited broader community engagement visible", "r": 4, "rn": "Highly relevant for emerging mobile and space networking requirements", "c": ["A2A protocols", "Autonomous netops"]}


draft_name: draft-han-rtgwg-codeployment-pfc-fgfc
prompt_hash: c4158b399832e443
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:58.237318+00:00
response_json:
  {"name": "draft-han-rtgwg-codeployment-pfc-fgfc", "s": "Describes use cases for coordinating flow control between data center PFC and WAN fine-grained flow control. Aims to achieve end-to-end lossless transmission across network domains.", "n": 3, "nn": "Addresses gap in cross-domain flow control coordination, building on established PFC mechanisms", "m": 3, "mn": "Well-structured requirements document but needs technical solution specification", "o": 2, "on": "Builds on existing PFC work but addresses novel cross-domain coordination problem", "mo": 3, "mon": "Addresses industry need for DC-WAN integration, likely to gain data center community interest", "r": 4, "rn": "Very relevant to current data center and cloud networking evolution", "c": ["ML traffic mgmt", "Data formats/interop"]}


draft_name: draft-ahc-green-smartpdu-yang
prompt_hash: 565bb6d85cafaea7
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:58.246181+00:00
response_json:
  {"name": "draft-ahc-green-smartpdu-yang", "s": "Defines YANG model for smart power distribution unit monitoring and control. Provides vendor-neutral framework developed during IETF hackathon for energy management.", "n": 2, "nn": "Straightforward application of YANG to power management domain, incremental innovation", "m": 3, "mn": "Has working implementation from hackathon but needs refinement for production use", "o": 1, "on": "Unique focus on SmartPDU YANG modeling with minimal overlap", "mo": 3, "mon": "Benefits from hackathon development and green networking interest", "r": 3, "rn": "Relevant to growing focus on network energy efficiency and sustainability", "c": ["Data formats/interop", "Policy/governance"]}


draft_name: draft-li-cdn-node-selection-enhancement
prompt_hash: b81ff57117c71965
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:45:58.255752+00:00
response_json:
  {"name": "draft-li-cdn-node-selection-enhancement", "s": "Proposes enhanced CDN node selection using anycast and QUIC for load-aware redirection. Enables dynamic route advertisement based on server load and client requirements.", "n": 3, "nn": "Clever combination of anycast, BGP, and QUIC for dynamic CDN optimization", "m": 2, "mn": "Early stage proposal with basic concepts outlined but needs detailed protocol specification", "o": 3, "on": "Overlaps with existing CDN and anycast technologies but offers novel integration approach", "mo": 2, "mon": "Limited visibility into industry adoption or working group interest", "r": 4, "rn": "Highly relevant to CDN performance optimization and modern application delivery", "c": ["ML traffic mgmt", "Autonomous netops"]}


draft_name: draft-kartha-internet20-ainative
prompt_hash: ba60486ecff8ad31
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:19.384398+00:00
response_json:
  {"name": "draft-kartha-internet20-ainative", "s": "Proposes Internet 2.0 architecture with AI models as first-class network entities, including HTTP+AI extensions, Model Resolution Network (MRN), and AI-aware browsers. Aims to transform the web from document retrieval to intent-based AI interaction.", "n": 4, "nn": "Novel concept of treating AI models as network primitives with dedicated discovery and routing mechanisms", "m": 2, "mn": "Highly ambitious architectural proposal lacking implementation details and concrete specifications", "o": 2, "on": "Some overlap with model serving concepts but unique in comprehensive internet architecture redesign", "mo": 3, "mon": "Addresses emerging need for AI-native networking but may be too ambitious for near-term adoption", "r": 4, "rn": "Highly relevant to future AI infrastructure needs and network evolution", "c": ["A2A protocols", "Model serving/inference", "Agent discovery/reg", "Data formats/interop"]}


draft_name: draft-xsaopig-nsttlp-traffic-labeling
prompt_hash: c74e44a504751358
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:19.397523+00:00
response_json:
  {"name": "draft-xsaopig-nsttlp-traffic-labeling", "s": "Specifies protocol for embedding service type identifiers in network packets to enable intelligent traffic recognition and policy-based forwarding. Supports various applications from VR to IoT with standardized service labels.", "n": 3, "nn": "Builds on existing traffic classification concepts but provides standardized labeling approach", "m": 4, "mn": "Well-defined protocol with clear packet header specifications and implementation guidance", "o": 3, "on": "Overlaps with existing QoS and traffic classification mechanisms but adds AI-awareness", "mo": 4, "mon": "Addresses practical network management needs with implementable solution", "r": 4, "rn": "Very relevant for AI workload management and network optimization", "c": ["ML traffic mgmt", "Autonomous netops", "Policy/governance"]}


draft_name: draft-vaughan-aipref-vocab
prompt_hash: d4f67763e8ecc730
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:19.407295+00:00
response_json:
  {"name": "draft-vaughan-aipref-vocab", "s": "Proposes vocabulary for rightsholders to express content preferences for AI training use through metadata or content-delivery protocols. Provides structured approach to permissions, usage scope, and data retention preferences.", "n": 3, "nn": "Addresses emerging need for AI training consent mechanisms with structured vocabulary approach", "m": 3, "mn": "Reasonably detailed vocabulary specification but needs broader ecosystem adoption", "o": 4, "on": "Significant overlap with related aipref drafts addressing similar content preference concerns", "mo": 4, "mon": "Strong relevance to current AI training and copyright concerns", "r": 5, "rn": "Extremely relevant to current debates over AI training data rights and consent", "c": ["Policy/governance", "Data formats/interop", "AI safety/alignment"]}


draft_name: draft-romm-aipref-contentsignals
prompt_hash: 5049cacace4634a3
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:19.418308+00:00
response_json:
  {"name": "draft-romm-aipref-contentsignals", "s": "Proposes three categories for expressing preferences about digital asset use by automated processing systems. Designed to nest within the broader AIPREF-VOCAB framework for automated processing preferences.", "n": 2, "nn": "Incremental extension to existing aipref work with limited novel contribution", "m": 2, "mn": "Very brief specification lacking detail and concrete implementation guidance", "o": 5, "on": "Heavy overlap with draft-vaughan-aipref-vocab, appears to be complementary work", "mo": 3, "mon": "Part of coordinated effort on content preferences but limited individual impact", "r": 4, "rn": "Relevant to AI training consent but adds limited value over related drafts", "c": ["Policy/governance", "Data formats/interop"]}


draft_name: draft-keller-aipref-vocab
prompt_hash: 920b06e0b89d087a
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:19.426963+00:00
response_json:
  {"name": "draft-keller-aipref-vocab", "s": "Proposes standardized vocabulary for machine-readable opt-outs related to Text and Data Mining and AI training. Defines three key use cases with mechanism-agnostic approach for consistent interpretation.", "n": 3, "nn": "Focuses specifically on opt-out mechanisms with clear use case categorization", "m": 2, "mn": "Brief specification needs more detailed implementation guidance and examples", "o": 4, "on": "Substantial overlap with other aipref drafts but focuses specifically on opt-out scenarios", "mo": 3, "mon": "Addresses important consent mechanisms but competes with similar efforts", "r": 4, "rn": "Relevant to AI training governance and rights management debates", "c": ["Policy/governance", "Data formats/interop", "AI safety/alignment"]}


draft_name: draft-liao-aipref-autoctl-ext
prompt_hash: d8038a7a9681b5de
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:39.316346+00:00
response_json:
  {"name": "draft-liao-aipref-autoctl-ext", "s": "Extends automation control protocols with granular permissions including rate limiting, technology restrictions, and API permissions. Provides service owners detailed control over automated interactions beyond basic core specifications.", "n": 3, "nn": "Reasonable extension of existing automation control concepts with practical granular controls", "m": 3, "mn": "References core spec but appears well-structured for an extension document", "o": 4, "on": "Heavy overlap with core automation control draft and general AI preference space", "mo": 3, "mon": "Part of related draft series with recent timestamps suggesting active development", "r": 4, "rn": "Highly relevant for AI automation management with practical granular controls", "c": ["ML traffic mgmt", "Policy/governance", "A2A protocols"]}


draft_name: draft-liao-aipref-autoctl-core
prompt_hash: 19f7db5b6e15097f
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:39.336856+00:00
response_json:
  {"name": "draft-liao-aipref-autoctl-core", "s": "Defines core machine-readable protocol for server-side automation permissions targeting AI-driven web automation. Builds on RFC9309 with file formats, HTTP method restrictions, and purpose requirements.", "n": 4, "nn": "Addresses emerging AI automation control needs with structured protocol approach", "m": 3, "mn": "Core specification appears reasonably complete with clear scope and structure", "o": 3, "on": "Overlaps with RFC9309 and AI preference space but defines distinct core protocol", "mo": 4, "mon": "Recent timestamp and companion extension draft suggest strong momentum", "r": 5, "rn": "Highly relevant core protocol for managing AI-driven automation interactions", "c": ["A2A protocols", "ML traffic mgmt", "Policy/governance"]}


draft_name: draft-it-aipref-attachment
prompt_hash: 9880f18001bea837
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:39.346914+00:00
response_json:
  {"name": "draft-it-aipref-attachment", "s": "Defines HTTP-based signaling mechanism for content usage preferences by automated systems. Updates RFC9309 to include usage preferences alongside content acquisition.", "n": 3, "nn": "Practical extension to existing RFC with focused HTTP integration approach", "m": 4, "mn": "Concise and focused update to established RFC with clear implementation path", "o": 4, "on": "Significant overlap with RFC9309 and broader AI preference signaling space", "mo": 2, "mon": "Older timestamp suggests less active recent development compared to other drafts", "r": 4, "rn": "Relevant for content creator rights and automated system compliance", "c": ["Policy/governance", "Data formats/interop", "Human-agent interaction"]}


draft_name: draft-illyes-aipref-cbcp
prompt_hash: 70bc959a493f4b44
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:39.355582+00:00
response_json:
  {"name": "draft-illyes-aipref-cbcp", "s": "Describes best practices for web crawlers with basic guidelines. Very brief document focusing on crawler behavior recommendations.", "n": 2, "nn": "Limited novelty as crawler best practices are well-established domain", "m": 2, "mn": "Very brief document with minimal technical depth, appears early stage", "o": 3, "on": "Moderate overlap with general web automation and crawler management practices", "mo": 2, "mon": "GitHub-hosted with recent timestamp but minimal content suggests limited momentum", "r": 3, "rn": "Moderately relevant for AI crawler behavior but lacks technical depth", "c": ["ML traffic mgmt", "Policy/governance"]}


draft_name: draft-thomson-aipref-sup
prompt_hash: a824086f852795f8
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:39.363844+00:00
response_json:
  {"name": "draft-thomson-aipref-sup", "s": "Defines simple format for content usage preference expressions with HTTP header field. Updates RFC9309 to provide standardized preference conveyance mechanism.", "n": 3, "nn": "Simple but practical approach to preference expression with HTTP integration", "m": 4, "mn": "Well-developed specification with detailed format definition and HTTP integration", "o": 4, "on": "High overlap with RFC9309 updates and AI preference signaling mechanisms", "mo": 3, "mon": "Recent timestamp and detailed specification suggest active development", "r": 4, "rn": "Highly relevant for standardizing AI content usage preference communication", "c": ["Data formats/interop", "Policy/governance", "Human-agent interaction"]}


draft_name: draft-ietf-aipref-vocab
prompt_hash: 3d48ffb256f2cc19
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:58.218435+00:00
response_json:
  {"name": "draft-ietf-aipref-vocab", "s": "Defines a standardized vocabulary for expressing preferences about how digital assets should be used by automated processing systems. Allows declaration of restrictions or permissions for AI and other automated systems.", "n": 4, "nn": "Core vocabulary specification is novel approach to standardizing AI usage preferences", "m": 4, "mn": "Well-developed 13-page spec from IETF working group with clear scope", "o": 2, "on": "Foundation vocabulary that other drafts build upon, minimal direct overlap", "mo": 5, "mon": "Official IETF working group draft with recent publication date", "r": 5, "rn": "Highly relevant as foundational specification for emerging AI content governance needs", "c": ["Policy/governance", "Data formats/interop", "Human-agent interaction"]}


draft_name: draft-ietf-aipref-attach
prompt_hash: 9487d9438b6aae9c
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:58.237344+00:00
response_json:
  {"name": "draft-ietf-aipref-attach", "s": "Specifies how AI usage preferences can be signaled during HTTP content acquisition. Updates RFC 9309 to include usage preference mechanisms for automated systems.", "n": 3, "nn": "Novel HTTP integration but builds on existing RFC 9309 foundation", "m": 4, "mn": "Mature IETF working group draft with clear technical specification", "o": 3, "on": "Complements vocab draft but focuses on HTTP transport mechanism", "mo": 5, "mon": "Active IETF working group effort with recent updates", "r": 4, "rn": "Very relevant for practical deployment of AI preference signaling", "c": ["A2A protocols", "Policy/governance", "Data formats/interop"]}


draft_name: draft-madhavan-aipref-displaybasedpref
prompt_hash: 1f70b4b230370bfd
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:58.246884+00:00
response_json:
  {"name": "draft-madhavan-aipref-displaybasedpref", "s": "Proposes vocabulary for controlling content usage by search and AI crawlers. Creates structured declarations about restrictions and permissions for crawler-retrieved content.", "n": 2, "nn": "Similar concept to IETF vocab draft but different approach and scope", "m": 3, "mn": "Individual submission with reasonable development but less institutional backing", "o": 4, "on": "Significant overlap with official IETF vocab draft in purpose and scope", "mo": 2, "mon": "Individual draft competing with established working group effort", "r": 3, "rn": "Relevant topic but potentially superseded by working group efforts", "c": ["Policy/governance", "ML traffic mgmt", "Data formats/interop"]}


draft_name: draft-illyes-aipref-jafar
prompt_hash: fdcf9ebecfcbf252
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:58.261059+00:00
response_json:
  {"name": "draft-illyes-aipref-jafar", "s": "Defines JSON format for automated HTTP client operators to publish their IP ranges publicly. Aims to help identify legitimate automated traffic and reduce blocking of beneficial clients.", "n": 3, "nn": "Novel standardization of existing practices for IP range disclosure", "m": 3, "mn": "Concise 8-page spec but individual submission lacks WG validation", "o": 2, "on": "Complementary to other drafts, focuses on client identification not preferences", "mo": 2, "mon": "Individual submission without clear working group adoption path", "r": 4, "rn": "Highly relevant for automated client identification and traffic management", "c": ["Agent identity/auth", "ML traffic mgmt", "Data formats/interop"]}


draft_name: draft-farzdusa-aipref-enduser
prompt_hash: d4f745768d17c856
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:46:58.272609+00:00
response_json:
  {"name": "draft-farzdusa-aipref-enduser", "s": "Documents potential end user impacts of AI preference signaling standards across technological, legal, and ethical dimensions. Suggests principles for working group consideration in standardization.", "n": 4, "nn": "Novel focus on end user impact analysis for AI preference standards", "m": 3, "mn": "Well-developed analysis but primarily guidance document rather than technical spec", "o": 1, "on": "Unique perspective focused on user impact rather than technical mechanisms", "mo": 3, "mon": "Recent individual submission addressing active working group concerns", "r": 4, "rn": "Highly relevant for ensuring standards consider broader stakeholder impacts", "c": ["Policy/governance", "Human-agent interaction"]}


draft_name: draft-altanai-aipref-realtime-protocol-bindings
prompt_hash: c1ae2056f34710df
model: claude-sonnet-4-20250514
request_json: batch[0]
created_at: 2026-03-03T19:47:03.479342+00:00
response_json:
  {"name": "draft-altanai-aipref-realtime-protocol-bindings", "s": "Defines how AI preference expressions are bound to real-time protocols like SIP and SDP. Specifies headers and attributes for endpoints and AI assistants to negotiate AI processing requirements for session metadata and media.", "n": 4, "nn": "Novel integration of AI preferences into established real-time communication protocols", "m": 3, "mn": "Well-structured with concrete protocol bindings but early stage implementation", "o": 2, "on": "Limited overlap, focuses specifically on real-time protocol bindings for AI preferences", "mo": 3, "mon": "Addresses emerging need for AI integration in telecom but niche application area", "r": 4, "rn": "Highly relevant as AI assistants become integrated into communication systems", "c": ["A2A protocols", "Human-agent interaction", "Data formats/interop"]}


draft_name: draft-aft-ai-traffic
prompt_hash: 0a3409539baba64d
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-aft-ai-traffic]
created_at: 2026-03-03T19:50:46.075690+00:00
response_json:
  [{"title": "AI Workload Characterization", "description": "Document specific network traffic characteristics of LLM training and inference workloads across federated datacenters.", "type": "requirement"}, {"title": "Inter-DC AI Traffic Problem Statement", "description": "Define networking challenges for distributing large parameter LLM models across multiple datacenters with collective communication libraries.", "type": "requirement"}, {"title": "Federated AI Service Architecture", "description": "Establish architectural patterns for cooperating service providers to jointly train, specialize, and serve LLM-based services.", "type": "architecture"}, {"title": "Private Data Training Network Requirements", "description": "Identify network requirements for secure training of AI models using private or protected data across administrative boundaries.", "type": "requirement"}]


draft_name: draft-altanai-aipref-realtime-protocol-bindings
prompt_hash: 05aa439122a0a62e
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-altanai-aipref-realtime-protocol-bindings]
created_at: 2026-03-03T19:50:46.110265+00:00
response_json:
  [{"title": "AI Preference Expression Binding Model", "description": "Define a reusable binding mechanism to attach AI preference expressions to real-time protocol signaling and media streams.", "type": "mechanism"}, {"title": "SIP Header AI Preference Convention", "description": "Specify standardized SIP header field conventions for advertising and negotiating AI-driven processing requirements in session initiation.", "type": "extension"}, {"title": "SDP AI Preference Attributes", "description": "Define SDP attributes allowing endpoints to express AI processing requirements for session metadata and media control events.", "type": "extension"}, {"title": "AI-Driven Session Metadata Processing", "description": "Enable intermediary services and AI assistants to enforce requirements about AI processing of session metadata and telemetry without disrupting call control.", "type": "pattern"}, {"title": "AIPREF Vocabulary Protocol Alignment", "description": "Establish protocol bindings that align real-time communication behavior with standardized AIPREF vocabulary for AI requirements.", "type": "protocol"}]


draft_name: draft-bernardos-nmrg-agentic-network-optimization
prompt_hash: e76b9bb0a0f1f77b
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-bernardos-nmrg-agentic-network-optimization]
created_at: 2026-03-03T19:50:46.115874+00:00
response_json:
  [{"title": "Distributed Sensing Task Orchestration", "description": "Enable coordination of multiple sensors to contribute raw or pre-processed sensing data to a centralized sensing service.", "type": "architecture"}, {"title": "Agentic Sensing Service Processing", "description": "Define mechanisms for executing distributed sensing services that fuse measurements from multiple networked sensors.", "type": "mechanism"}, {"title": "ISAC Network Optimization", "description": "Establish joint optimization of sensing and communication functions using shared spectral and hardware resources in wireless networks.", "type": "mechanism"}, {"title": "Environment Perception with ISAC", "description": "Enable advanced sensing capabilities for object tracking and situational awareness while maintaining efficient data transmission.", "type": "pattern"}, {"title": "Sensing Processing Placement Strategy", "description": "Define architectural patterns for determining optimal placement of sensing processing and computation nodes in network topology.", "type": "architecture"}]


draft_name: draft-calabria-bmwg-ai-fabric-inference-bench
prompt_hash: 6f6464de177aa731
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-calabria-bmwg-ai-fabric-inference-bench]
created_at: 2026-03-03T19:50:59.309499+00:00
response_json:
  [{"title": "Time to First Token (TTFT) Measurement", "description": "Standardized methodology for measuring latency from inference request submission to first token generation in disaggregated prefill/decode architectures.", "type": "mechanism"}, {"title": "Inter-Token Latency (ITL) Benchmarking", "description": "KPI definition and measurement procedure for latency between successive token outputs in LLM inference serving.", "type": "mechanism"}, {"title": "Throughput per Second (TPS) KPI", "description": "Standardized metric for aggregate token generation rate across distributed inference fabric under realistic workloads.", "type": "mechanism"}, {"title": "RDMA KV Cache Transfer Testing", "description": "Vendor-independent test procedures for benchmarking RDMA-based key-value cache transfers between disaggregated prefill and decode workers.", "type": "mechanism"}, {"title": "Fabric Bottleneck Characterization", "description": "Methodology to isolate and quantify how Ethernet fabric interconnect performance constrains end-to-end inference latency and throughput.", "type": "pattern"}, {"title": "AI Inference Workload Modeling", "description": "Reproducible test procedures simulating realistic disaggregated LLM inference workloads across hundreds or thousands of accelerators.", "type": "mechanism"}, {"title": "Vendor-Neutral Fabric Comparison Framework", "description": "Standardized benchmarking procedures enabling reproducible, vendor-independent evaluation of different Ethernet-based AI fabric architectures.", "type": "pattern"}]


draft_name: draft-calabria-bmwg-ai-fabric-terminology
prompt_hash: 51fa1711c98c0b8f
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-calabria-bmwg-ai-fabric-terminology]
created_at: 2026-03-03T19:50:59.327518+00:00
response_json:
  [{"title": "Collective Communication Primitives Definition", "description": "Unified vendor-neutral terminology for collective communication operations (allreduce, allgather, broadcast, etc.) used in distributed AI training and inference.", "type": "requirement"}, {"title": "RoCEv2 Transport Terminology", "description": "Precise definitions and performance characteristics for RDMA over Converged Ethernet version 2 as applied to AI fabric workloads.", "type": "requirement"}, {"title": "Ultra Ethernet Transport Terminology", "description": "Standardized terminology and definitions for Ultra Ethernet Transport mechanisms in AI inference and training fabrics.", "type": "requirement"}, {"title": "AI-Specific KPI Taxonomy", "description": "Consolidated and extended definitions for AI workload KPIs including TTFT, ITL, TPS, and fabric-specific performance metrics.", "type": "requirement"}, {"title": "Congestion Control Behavior Definitions", "description": "Vendor-neutral definitions for congestion control mechanisms and their measurable behaviors in AI fabric environments.", "type": "requirement"}, {"title": "Fabric Topology Concepts Vocabulary", "description": "Standardized terminology for describing fabric topology patterns, hierarchies, and configurations used in distributed AI systems.", "type": "requirement"}, {"title": "RFC 1242 and RFC 8238 Extension", "description": "Extension and consolidation of existing benchmarking terminology standards (RFC 1242, RFC 8238) with AI-specific additions.", "type": "extension"}]


draft_name: draft-cgfabk-nmrg-ibn-generative-ai
prompt_hash: c50ca14ae2a46081
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-cgfabk-nmrg-ibn-generative-ai]
created_at: 2026-03-03T19:50:59.334694+00:00
response_json:
  [{"title": "Intent-Based Networking AI Specialization", "description": "Methodology for training and specializing generative AI models to interpret and act on high-level network intents.", "type": "pattern"}, {"title": "Scalable Intent Model Architecture", "description": "Architecture for creating efficiently deployable generative AI models targeting specific Intent-Based Networking domains.", "type": "architecture"}, {"title": "Targeted Generative Model Framework", "description": "Framework for constraining and optimizing generative AI models to produce domain-specific Intent-Based Networking outputs.", "type": "mechanism"}, {"title": "Intent Interpretation Pipeline", "description": "Process for translating natural language or structured intents into actionable network configuration via specialized AI models.", "type": "pattern"}]


draft_name: draft-chen-nmrg-multi-provider-inference-api
prompt_hash: 085ff5a2cd7d052c
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-chen-nmrg-multi-provider-inference-api]
created_at: 2026-03-03T19:50:59.342107+00:00
response_json:
  [{"title": "OpenAI API Multi-Provider Extension", "description": "Extension specification enabling multiple distributed inference providers to be orchestrated through the OpenAI Responses API interface.", "type": "extension"}, {"title": "Provider Diversity Negotiation", "description": "Mechanism for clients to specify provider preferences and negotiate capability support across multiple inference providers.", "type": "mechanism"}, {"title": "Intelligent Load Balancing", "description": "Algorithm for distributing inference requests across multiple providers based on latency, cost, and capability metrics.", "type": "mechanism"}, {"title": "Automatic Failover Protocol", "description": "Procedure for transparently failing over inference requests to alternative providers upon primary provider failure.", "type": "mechanism"}, {"title": "Capability Negotiation Extension", "description": "Extension allowing clients to query and negotiate AI model capabilities, versions, and features across heterogeneous providers.", "type": "mechanism"}, {"title": "Backward-Compatible API Enhancement", "description": "Design pattern ensuring multi-provider orchestration extensions do not require changes to existing client applications or standard API usage.", "type": "pattern"}]


draft_name: draft-chen-nmrg-semantic-inference-routing
prompt_hash: 99376e801559ac3b
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-chen-nmrg-semantic-inference-routing]
created_at: 2026-03-03T19:50:59.349310+00:00
response_json:
  [{"title": "Semantic Inference Routing Protocol (SIRP)", "description": "Framework for analyzing inference request content to make intelligent routing decisions independent of client-supplied metadata.", "type": "protocol"}, {"title": "Content-Level Request Classification", "description": "Mechanism for automatically classifying inference requests by semantic content rather than relying on explicit client metadata.", "type": "mechanism"}, {"title": "Semantic Content Router", "description": "Routing entity that inspects inference request content and selects destinations based on semantic analysis.", "type": "mechanism"}, {"title": "Cost Optimization Routing Extension", "description": "Value-added routing extension that routes inference requests to minimize monetary cost while meeting quality requirements.", "type": "extension"}, {"title": "Urgency-Aware Request Prioritization", "description": "Value-added routing extension that prioritizes urgent inference requests for lower-latency path selection.", "type": "extension"}, {"title": "Domain Specialization Routing", "description": "Value-added routing extension that routes requests to inference endpoints specialized for specific domains or task types.", "type": "extension"}, {"title": "Privacy-Aware Inference Routing", "description": "Value-added routing extension that enforces privacy policies by routing sensitive inference requests to compliant infrastructure.", "type": "extension"}, {"title": "Robust Semantic Routing Decision Making", "description": "Routing architecture that improves consistency and extensibility by basing routing decisions on request content analysis rather than metadata.", "type": "architecture"}]


draft_name: draft-chen-tsvwg-high-speed-data-express
prompt_hash: 8fcd0400654f4d6e
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-chen-tsvwg-high-speed-data-express]
created_at: 2026-03-03T19:51:09.001533+00:00
response_json:
  [{"title": "High Elasticity Data Express Architecture", "description": "A reference architecture for wide-area IP-based data transmission optimized for massive data movement in AI and supercomputing workloads.", "type": "architecture"}, {"title": "One Low Three High Technical System", "description": "A technical framework emphasizing low latency with three high dimensions (high throughput, high reliability, high efficiency) for differentiated data express services.", "type": "pattern"}, {"title": "IP Network Statistical Reuse", "description": "Mechanism leveraging statistical multiplexing advantages inherent in IP networks for efficient resource allocation in high-speed data transmission.", "type": "mechanism"}, {"title": "Elastic Supply for Data Express", "description": "Dynamic resource provisioning mechanism that adapts bandwidth and capacity allocation based on fluctuating data transmission demands.", "type": "mechanism"}, {"title": "Task-Type Data Express Services", "description": "Service differentiation model that classifies and prioritizes data express services according to specific task requirements and characteristics.", "type": "extension"}]


draft_name: draft-chuyi-nmrg-agentic-network-inference
prompt_hash: a25a2b3c2d2820f1
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-chuyi-nmrg-agentic-network-inference]
created_at: 2026-03-03T19:51:09.012439+00:00
response_json:
  [{"title": "Agentic Network Architecture", "description": "Network architecture designed to support interconnection and coordination of multiple AI agents with low latency and high bandwidth requirements.", "type": "architecture"}, {"title": "Multi-level Inference Protocol", "description": "Protocol enabling efficient inference operations across multiple agent levels with cross-domain coordination and scheduling capabilities.", "type": "protocol"}, {"title": "Cross-Domain Agent Coordination", "description": "Mechanism for orchestrating collaborative tasks among agents operating across different administrative and technical domains.", "type": "mechanism"}, {"title": "Agent Orchestration Framework", "description": "Management framework providing centralized control and scheduling for complex multi-agent collaborative workflows.", "type": "architecture"}, {"title": "Information Exchange Efficiency", "description": "Optimization techniques for reducing overhead in message passing and state synchronization between interconnected intelligent agents.", "type": "mechanism"}]


draft_name: draft-cowles-volt
prompt_hash: 33e41033be67afcb
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-cowles-volt]
created_at: 2026-03-03T19:51:09.018669+00:00
response_json:
  [{"title": "VOLT Protocol Format", "description": "Minimal interoperable format for producing tamper-evident execution traces of AI agent workflows with cryptographic integrity guarantees.", "type": "protocol"}, {"title": "SHA-256 Hash Chain Linking", "description": "Mechanism that cryptographically links sequential event records using SHA-256 hash chains to prevent modification or deletion.", "type": "mechanism"}, {"title": "Evidence Bundle Packaging", "description": "Method for packaging linked execution records into portable, independently verifiable bundles for audit and compliance purposes.", "type": "mechanism"}, {"title": "AI Agent Flight Recorder", "description": "Comprehensive logging system capturing messages, policy decisions, human approvals, tool invocations, and results with forensic capabilities.", "type": "pattern"}, {"title": "Privacy-First Event Metadata", "description": "Design pattern using content-addressed references and metadata instead of raw content to maintain privacy while preserving auditability.", "type": "pattern"}, {"title": "Post-Hoc Modification Detection", "description": "Security mechanism enabling detection of tampering attempts including insertion, deletion, or alteration of historical event records.", "type": "mechanism"}]


draft_name: draft-du-catalist-routing-considerations
prompt_hash: 7c37f1518a848ae1
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-du-catalist-routing-considerations]
created_at: 2026-03-03T19:51:09.030714+00:00
response_json:
  [{"title": "Agent-to-Agent Routing Protocol", "description": "Routing protocol specifically designed to handle communication flows between AI agents with distinct skills and capabilities.", "type": "protocol"}, {"title": "Cross-Domain Agent Routing", "description": "Routing mechanism addressing multi-domain scenarios where agentic networks operate as overlay networks above IP infrastructure.", "type": "mechanism"}, {"title": "Agentic Network Overlay Architecture", "description": "Architecture pattern defining agentic networks as application-layer overlays that abstract underlying IP network heterogeneity.", "type": "architecture"}, {"title": "Agent Capability-Based Routing", "description": "Routing strategy that selects paths and next-hop agents based on advertised capabilities and task requirements rather than traditional network topology.", "type": "mechanism"}, {"title": "New Agent Traffic Requirements", "description": "Requirements specification for novel quality-of-service, latency, and bandwidth needs introduced by agent-to-agent communication patterns.", "type": "requirement"}]


draft_name: draft-farzdusa-aipref-enduser
prompt_hash: 49ecaaa620d395cd
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-farzdusa-aipref-enduser]
created_at: 2026-03-03T19:51:29.726429+00:00
response_json:
  [{"title": "End User Impact Assessment Framework", "description": "Principles for evaluating AI preference signaling standards across technological, legal, ethical, and governance dimensions.", "type": "requirement"}, {"title": "User Control over Digital Contributions", "description": "Mechanisms enabling end users to assert preferences about how their data is used by AI systems.", "type": "requirement"}, {"title": "Data Privacy Signaling Requirements", "description": "Standards for expressing privacy preferences distinct from publisher-focused AI preference signals.", "type": "requirement"}, {"title": "Multi-stakeholder Impact Assessment", "description": "Framework to assess AI preference standards on end user classes beyond content publishers.", "type": "pattern"}]


draft_name: draft-han-anima-ai-asa
prompt_hash: a73cc84c9c1124da
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-han-anima-ai-asa]
created_at: 2026-03-03T19:51:29.742202+00:00
response_json:
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draft_name: draft-han-rtgwg-codeployment-pfc-fgfc
prompt_hash: 21e14702b8ed60ce
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-han-rtgwg-codeployment-pfc-fgfc]
created_at: 2026-03-03T19:51:29.747924+00:00
response_json:
  [{"title": "Fine-Grained Flow Control Mechanism", "description": "Flow control mechanism enabling precise control at flow/tenant levels with path and slice restrictions.", "type": "mechanism"}, {"title": "Cross-DCN-WAN Flow Control Collaboration", "description": "Requirements and architecture for coordinating PFC mechanisms in Data Center Networks with fine-grained flow control in Wide Area Networks.", "type": "architecture"}, {"title": "Intelligent Congestion Backpressure", "description": "Mechanism for intelligent backpressure signaling across DCN and WAN boundaries to manage congestion.", "type": "mechanism"}, {"title": "End-to-End Lossless Flow Control Requirements", "description": "Requirements for achieving lossless transmission through coordinated flow control across heterogeneous network domains.", "type": "requirement"}, {"title": "Flow/Tenant-Level Control Isolation", "description": "Mechanism to limit flow control effects to specified paths and tenant boundaries in WANs.", "type": "mechanism"}]


draft_name: draft-howe-sipcore-mcp-extension
prompt_hash: d66d1692364f9041
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-howe-sipcore-mcp-extension]
created_at: 2026-03-03T19:51:29.761339+00:00
response_json:
  [{"title": "SIP Option-Tag for MCP", "description": "New SIP option-tag 'mcp' to advertise support for Model Context Protocol in SIP implementations.", "type": "extension"}, {"title": "MCP Capability Advertisement Headers", "description": "New SIP header fields for advertising and selecting Model Context Protocol capabilities.", "type": "extension"}, {"title": "MCP Registration-Time Discovery", "description": "Contact feature-capability parameters enabling MCP capability discovery during SIP registration.", "type": "mechanism"}, {"title": "Application/MCP+JSON Media Type", "description": "Media type definition for carrying Model Context Protocol payloads in JSON format.", "type": "extension"}, {"title": "MCP Exchange in Session Establishment", "description": "Mechanism for negotiating and exchanging MCP payloads during SIP session establishment via INVITE/200.", "type": "protocol"}, {"title": "Mid-Dialog MCP Exchange", "description": "Protocol extension enabling MCP payload exchange mid-dialog using MESSAGE and INFO methods.", "type": "protocol"}, {"title": "MCP Offer/Answer Negotiation", "description": "Offer/Answer model negotiation for MCP support and configuration within SIP sessions.", "type": "mechanism"}]


draft_name: draft-hu-neotec-usecases-notc
prompt_hash: 431282946665402c
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-hu-neotec-usecases-notc]
created_at: 2026-03-03T19:51:40.141778+00:00
response_json:
  [{"title": "Dynamic Resource Scheduling Across Heterogeneous Computing", "description": "Mechanism for scheduling AI inference workloads across heterogeneous compute resources (GPUs/NPUs) and network domains in telco cloud environments.", "type": "mechanism"}, {"title": "Centralized Training with Distributed Inference", "description": "Architecture pattern enabling centralized model training with inference execution distributed across edge and core network nodes.", "type": "architecture"}, {"title": "Low-Latency Data Transmission with Data Sovereignty", "description": "Protocol mechanism ensuring data transmission meets latency requirements while enforcing data residency and sovereignty constraints.", "type": "mechanism"}, {"title": "Elastic Bandwidth Provisioning", "description": "Dynamic bandwidth allocation mechanism that adapts to workload demands in real-time across network infrastructure.", "type": "mechanism"}, {"title": "Network Failover with QoS Assurance", "description": "Failover mechanism maintaining Quality of Service guarantees during network or compute node failures.", "type": "mechanism"}, {"title": "Standardized Cloud-Network Controller Interface", "description": "Protocol interface specification enabling coordinated resource optimization between cloud and network controllers.", "type": "protocol"}, {"title": "AI-Based Video Recognition in Smart City Management", "description": "Use case pattern for deploying distributed video analytics with centralized model training across telecom cloud infrastructure.", "type": "pattern"}]


draft_name: draft-ietf-aipref-attach
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model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-ietf-aipref-attach]
created_at: 2026-03-03T19:51:40.157677+00:00
response_json:
  [{"title": "HTTP Content Acquisition with Usage Preferences", "description": "Extension to HTTP protocol allowing content creators to signal AI usage preferences during content delivery.", "type": "extension"}, {"title": "RFC 9309 Update for Preference Signaling", "description": "Modification of existing robots.txt standard to include machine-readable usage preference declarations.", "type": "extension"}, {"title": "Content Creator Preference Declaration", "description": "Mechanism enabling stakeholders to express restrictions or permissions for automated system consumption of their content.", "type": "mechanism"}, {"title": "Preference Signal Integration in Content Fetch", "description": "Protocol pattern embedding preference metadata within HTTP response headers or content payloads.", "type": "pattern"}]


draft_name: draft-ietf-aipref-vocab
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model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-ietf-aipref-vocab]
created_at: 2026-03-03T19:51:40.163760+00:00
response_json:
  [{"title": "AI Usage Preferences Vocabulary", "description": "Standardized vocabulary defining terms for expressing permissions and restrictions on digital asset usage by automated systems.", "type": "protocol"}, {"title": "Digital Asset Usage Declaration", "description": "Structured format allowing declaration of how digital assets may be processed, analyzed, or included in training by AI systems.", "type": "mechanism"}, {"title": "Restriction and Permission Expressions", "description": "Vocabulary elements enabling granular specification of allowed and prohibited uses for digital content.", "type": "protocol"}, {"title": "Automated Processing System Constraints", "description": "Vocabulary for defining operational constraints and boundaries for machine learning and AI processing activities.", "type": "protocol"}]


draft_name: draft-illyes-aipref-jafar
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model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-illyes-aipref-jafar]
created_at: 2026-03-03T19:51:40.173958+00:00
response_json:
  [{"title": "JSON IP Range Publication Format", "description": "Standardized JSON schema for automated HTTP client operators to publish their IP address ranges in machine-readable format.", "type": "protocol"}, {"title": "Automated Client IP Range Registry", "description": "Mechanism enabling legitimate bots and crawlers to register and advertise their IP ranges for identification by website operators.", "type": "mechanism"}, {"title": "IP Range Verification for Legitimate Traffic", "description": "Protocol pattern simplifying identification and verification of legitimate automated traffic through standardized IP range declarations.", "type": "mechanism"}, {"title": "Extensible Automated Client Metadata", "description": "JSON format supporting extension fields for operators to declare additional operational metadata beyond IP ranges.", "type": "protocol"}, {"title": "Reduction of Inadvertent Legitimate Traffic Blocking", "description": "Architecture pattern reducing false-positive blocking of beneficial automated clients through standardized IP disclosure.", "type": "architecture"}, {"title": "Crawler and Bot Operator Transparency", "description": "Standardized mechanism for web crawler and AI bot operators to declare ownership and operational details publicly.", "type": "mechanism"}]


draft_name: draft-improving-data-quality-tags
prompt_hash: 04352106d19d0255
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-improving-data-quality-tags]
created_at: 2026-03-03T19:51:52.248241+00:00
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  [{"title": "Special Text Tags for Data Quality", "description": "Use structured XML/markup-style tags to annotate training data and user queries with semantic information to improve model understanding and response accuracy.", "type": "pattern"}, {"title": "Context-Enhanced Training Data", "description": "Incorporate contextual metadata tags during model training to provide explicit semantic signals about data provenance, quality, and intent.", "type": "extension"}, {"title": "Query Intent Tagging", "description": "Apply special tags to user queries in conversational AI to mark intent, domain, and confidence levels for improved routing and response generation.", "type": "mechanism"}, {"title": "Inference-Time Tag Processing", "description": "Process structural tags during model inference to dynamically adjust response behavior based on tagged context markers.", "type": "mechanism"}]


draft_name: draft-intellinode-ai-semantic-contract
prompt_hash: 36b0a21a9ef69228
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-intellinode-ai-semantic-contract]
created_at: 2026-03-03T19:51:52.264114+00:00
response_json:
  [{"title": "Semantic-Driven Shaping Contract", "description": "Define a network contract where applications expose minimum necessary tensor semantics to enable fine-grained differentiated forwarding and resource allocation.", "type": "protocol"}, {"title": "Tensor Flow Semantic Signaling", "description": "Allow distributed training frameworks to explicitly communicate tensor flow semantics, training phases, and priority to network infrastructure.", "type": "mechanism"}, {"title": "Predefined Semantic Rules Engine", "description": "Implement rule-based network actions triggered by semantic signals from AI applications to optimize scheduling and resource allocation.", "type": "mechanism"}, {"title": "Global Real-Time State Awareness", "description": "Maintain distributed state tracking across heterogeneous computing networks to enable context-aware forwarding decisions based on current cluster conditions.", "type": "architecture"}, {"title": "Cross-Domain Intelligent Computing Coordination", "description": "Extend semantic contract support across multiple computing centers and domains to optimize integrated training-inference scenarios.", "type": "architecture"}]


draft_name: draft-intellinode-cats-in-network-scheduling
prompt_hash: 09495ee50ed24231
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-intellinode-cats-in-network-scheduling]
created_at: 2026-03-03T19:51:52.270498+00:00
response_json:
  [{"title": "In-Network Intelligent Scheduling on CATS", "description": "Build intelligent scheduling mechanism upon Computing-Aware Traffic Steering framework to optimize tensor flow routing in heterogeneous AI clusters.", "type": "extension"}, {"title": "Tensor Semantics Awareness", "description": "Equip network infrastructure with understanding of tensor semantics and training phases to enable semantically-informed scheduling decisions.", "type": "mechanism"}, {"title": "Heterogeneous Computing Capability Registration", "description": "Maintain network-wide registry of GPU/CPU/FPGA capabilities and their current utilization to enable capability-aware traffic steering.", "type": "mechanism"}, {"title": "Data-Plane Closed-Loop Decision Loop", "description": "Implement rapid perception-inference-decision-execution cycle in programmable switch ASICs and FPGAs to minimize scheduling latency.", "type": "architecture"}, {"title": "FPGA-Accelerated In-Network Processing", "description": "Integrate FPGAs alongside programmable switch ASICs to enable high-speed tensor semantic parsing and scheduling decision computation.", "type": "mechanism"}, {"title": "Passive-to-Active Scheduling Paradigm", "description": "Replace reactive probe-based and controller-based scheduling with proactive data-plane intelligence for immediate response to training conditions.", "type": "pattern"}]


draft_name: draft-irtf-nmrg-ai-deploy
prompt_hash: 9cc037382b516b72
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-irtf-nmrg-ai-deploy]
created_at: 2026-03-03T19:51:52.277002+00:00
response_json:
  [{"title": "Distributed AI Inference Architecture", "description": "Design network and system configurations for deploying AI inference services across edge devices, commodity servers, and cloud infrastructure.", "type": "architecture"}, {"title": "Heterogeneous Hardware Support", "description": "Establish configuration guidelines for running AI services on diverse hardware ranging from microcontrollers and low-performance CPUs to specialized AI chipsets.", "type": "requirement"}, {"title": "Client-Server-Edge Routing Selection", "description": "Define decision factors for directing AI service requests to appropriate endpoints (cloud servers vs. edge devices) based on latency, capability, and load.", "type": "mechanism"}, {"title": "Autonomous Vehicle AI Service Deployment", "description": "Specify network and system considerations for deploying real-time AI inference in vehicular networks with strict latency and reliability requirements.", "type": "pattern"}, {"title": "Network Digital Twin Support", "description": "Enable deployment of AI-based digital twins as network services for real-time network simulation and optimization.", "type": "pattern"}, {"title": "Resource-Constrained Device Optimization", "description": "Provide configuration guidelines for AI inference on affordable low-power hardware including microcontrollers with limited compute and memory.", "type": "requirement"}]


draft_name: draft-it-aipref-attachment
prompt_hash: da9157efbbce89f2
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-it-aipref-attachment]
created_at: 2026-03-03T19:51:52.283361+00:00
response_json:
  [{"title": "HTTP Content Usage Preference Signaling", "description": "Define HTTP header mechanisms to signal creator preferences about how content may be consumed by automated systems and AI models.", "type": "protocol"}, {"title": "Content Acquisition Preference Attachment", "description": "Allow preferences to be communicated during HTTP content retrieval to inform downstream usage by automated systems.", "type": "extension"}, {"title": "Creator Intent Preference Metadata", "description": "Enable content creators to express preferences regarding training data usage, indexing, aggregation, and automated analysis.", "type": "mechanism"}, {"title": "RFC 9309 Usage Preference Extension", "description": "Extend existing RFC 9309 specifications to include machine-readable usage preference signals in HTTP responses.", "type": "extension"}, {"title": "Automated System Preference Compliance", "description": "Establish mechanism for automated systems to discover and respect creator preferences signaled through HTTP content acquisition.", "type": "requirement"}]


draft_name: draft-jadoon-nmrg-agentic-ai-autonomous-networks
prompt_hash: 481de76d843441d5
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-jadoon-nmrg-agentic-ai-autonomous-networks]
created_at: 2026-03-03T19:52:05.360037+00:00
response_json:
  [{"title": "AI Agents as Protocol Layer Entities", "description": "Introduce AI agents as first-class entities at each layer of the IP protocol stack, enabling autonomous decision-making within existing protocol boundaries.", "type": "architecture"}, {"title": "Agent Controller Coordination", "description": "Implement one or more centralized or distributed agent controllers to coordinate behavior across multiple autonomous agents spanning different protocol layers.", "type": "mechanism"}, {"title": "Deterministic Protocol Layering Preservation", "description": "Maintain the integrity of traditional protocol layering for interoperability while augmenting with AI capabilities at each layer.", "type": "requirement"}, {"title": "Goal-Driven Closed-Loop Operations", "description": "Enable autonomous networks to operate via feedback loops that pursue system-defined goals across multiple protocol layers and administrative domains.", "type": "pattern"}, {"title": "Planning and Tool Invocation Framework", "description": "Define mechanisms for agentic systems to perform planning, reasoning, and invoke network tools to achieve network objectives.", "type": "mechanism"}, {"title": "Agentic Augmentation Pattern", "description": "Provide an architectural pattern for augmenting the existing IP suite with agentic capabilities while maintaining protocol interoperability.", "type": "pattern"}]


draft_name: draft-jain-lisp-network-ai-infra
prompt_hash: 930993009ed69de4
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-jain-lisp-network-ai-infra]
created_at: 2026-03-03T19:52:05.377639+00:00
response_json:
  [{"title": "LISP-Based Unified Control Plane", "description": "Leverage LISP control plane mechanisms to create a unified architecture supporting Scale-Up, Scale-Out, and Scale-Across deployment models for AI infrastructure.", "type": "architecture"}, {"title": "EID-to-RLOC Mapping for AI Networks", "description": "Use LISP EID-to-RLOC mappings and proxy tunnel router registrations to enable flexible network topology management for AI workloads.", "type": "mechanism"}, {"title": "Publication-Subscription for AI Data Flow", "description": "Implement LISP publication-subscription mechanisms to efficiently manage collective operations and data distribution across AI training clusters.", "type": "mechanism"}, {"title": "VPN Instance-Based Segmentation", "description": "Apply LISP VPN instance segmentation to isolate and manage multiple AI workloads with different QoS and latency requirements.", "type": "extension"}, {"title": "Scalable High-Bandwidth Training Support", "description": "Enable LISP-based network architecture to deliver scalable high-bandwidth connectivity required for large-scale distributed AI training workloads.", "type": "requirement"}, {"title": "Ultra-Low-Latency Collective Operations", "description": "Optimize LISP control plane to support ultra-low-latency collective communication operations essential for distributed AI model training.", "type": "requirement"}, {"title": "Heterogeneous Backend Network Integration", "description": "Design LISP-based framework to seamlessly span and integrate heterogeneous backend networks within AI infrastructure environments.", "type": "extension"}]


draft_name: draft-jennings-ai-mcp-over-moq
prompt_hash: 7fc30109f6113950
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-jennings-ai-mcp-over-moq]
created_at: 2026-03-03T19:52:05.384383+00:00
response_json:
  [{"title": "MCP Message Mapping to MOQT Objects", "description": "Define the encoding and mapping of Model Context Protocol messages into Media over QUIC Transport objects for efficient transport.", "type": "mechanism"}, {"title": "MCP Session Establishment over MOQT", "description": "Specify procedures for establishing, maintaining, and terminating MCP sessions using MOQT as the underlying transport protocol.", "type": "protocol"}, {"title": "MCP Resources Transport", "description": "Enable transport of MCP resource primitives through dedicated MOQT tracks with appropriate delivery guarantees.", "type": "mechanism"}, {"title": "MCP Tools Delivery over MOQT", "description": "Define how MCP tool invocation primitives are transported through MOQT with priority management and reliable delivery.", "type": "mechanism"}, {"title": "MCP Prompts Distribution", "description": "Specify transport of MCP prompt primitives over MOQT tracks with latency optimization for interactive AI applications.", "type": "mechanism"}, {"title": "MCP Notifications over MOQT", "description": "Define efficient delivery of MCP notification primitives using MOQT's publish-subscribe model for real-time updates.", "type": "mechanism"}, {"title": "Priority Management for MCP Primitives", "description": "Implement priority-based scheduling for different MCP message types across dedicated MOQT tracks to optimize latency and throughput.", "type": "mechanism"}, {"title": "Low-Latency LLM-Tool Integration", "description": "Leverage MOQT's low-latency characteristics to enable seamless real-time integration between language models and external tools.", "type": "pattern"}]


draft_name: draft-jennings-mcp-over-moqt
prompt_hash: 40b64f282c3de781
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-jennings-mcp-over-moqt]
created_at: 2026-03-03T19:52:05.391061+00:00
response_json:
  [{"title": "MCP-to-MOQT Protocol Mapping", "description": "Define the technical mapping between Model Context Protocol semantics and Media over QUIC Transport objects.", "type": "protocol"}, {"title": "MCP Session Management over MOQT", "description": "Establish procedures for creating and maintaining MCP communication sessions using MOQT transport.", "type": "protocol"}, {"title": "Publish-Subscribe Transport for MCP", "description": "Utilize MOQT's native publish-subscribe capabilities to distribute MCP resources, tools, and prompts to multiple consumers.", "type": "pattern"}, {"title": "WebTransport Compatibility", "description": "Enable MCP operation over both QUIC and WebTransport backends through MOQT for cross-platform AI tool integration.", "type": "extension"}, {"title": "LLM-External Tool Integration Transport", "description": "Provide efficient transport mechanism for seamless integration between language models and external data sources or tools.", "type": "protocol"}]


draft_name: draft-jimenez-tbd-robotstxt-update
prompt_hash: 398995766f2a91bd
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-jimenez-tbd-robotstxt-update]
created_at: 2026-03-03T19:52:05.396968+00:00
response_json:
  [{"title": "AI-Specific User-Agent Identification", "description": "Extend robots.txt syntax to enable identification and differentiation of AI-specific crawlers from traditional web crawlers.", "type": "extension"}, {"title": "Training vs. Inference Activity Distinction", "description": "Define robots.txt policy syntax to differentiate between AI crawler activities for model training versus inference-time operations.", "type": "extension"}, {"title": "AI Crawler Policy Differentiation", "description": "Introduce mechanisms for web content publishers to apply different access policies to AI systems compared to traditional crawlers.", "type": "mechanism"}, {"title": "Enhanced User-Agent Syntax", "description": "Expand robots.txt syntax to support more granular user-agent identification patterns specific to AI crawler identification.", "type": "extension"}, {"title": "Content Access Management for AI Systems", "description": "Enable web publishers to explicitly manage and control access to their content by AI training and inference systems.", "type": "requirement"}]


draft_name: draft-kartha-internet20-ainative
prompt_hash: 9e0cc7fae2936eaf
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-kartha-internet20-ainative]
created_at: 2026-03-03T19:52:16.214601+00:00
response_json:
  [{"title": "HTTP+AI Protocol Extension", "description": "An extension to HTTP that adds protocol-level awareness of AI models and enables AI-native communication patterns.", "type": "protocol"}, {"title": "Model Resolution Network (MRN)", "description": "A DNS-analogous system for discovering and resolving AI models across distributed networks.", "type": "architecture"}, {"title": "AI-Aware Browser", "description": "A new client architecture optimized for semantic interaction with AI systems rather than document traversal.", "type": "architecture"}, {"title": "Intent-Based Routing", "description": "A routing mechanism that interprets user intent and directs requests to appropriate AI models and resources.", "type": "mechanism"}, {"title": "AI Models as First-Class Entities", "description": "An architectural pattern treating AI models with network-level primitives similar to traditional web services.", "type": "architecture"}, {"title": "Decentralized AI Layer", "description": "A protocol-level semantic layer providing privacy-preserving AI interaction without centralized intermediaries.", "type": "architecture"}]


draft_name: draft-keller-aipref-vocab
prompt_hash: 0ab173b8dc5d4e7d
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-keller-aipref-vocab]
created_at: 2026-03-03T19:52:16.231552+00:00
response_json:
  [{"title": "Standardized TDM/AI Opt-Out Vocabulary", "description": "A machine-readable vocabulary defining use cases for Text and Data Mining and AI training opt-outs.", "type": "pattern"}, {"title": "Three-Level Use Case Taxonomy", "description": "Defines three distinct use case categories (TDM, AI Training, Generative AI Training) for opt-out expression.", "type": "requirement"}, {"title": "Mechanism-Agnostic Opt-Out Framework", "description": "A vocabulary layer that remains independent of specific opt-out implementation mechanisms.", "type": "pattern"}, {"title": "Interoperable Permission Declaration", "description": "A structured format enabling consistent interpretation of restrictions and permissions across different opt-out systems.", "type": "mechanism"}]


draft_name: draft-li-cats-aisemantic-contract
prompt_hash: 248e6f270c11bcee
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-li-cats-aisemantic-contract]
created_at: 2026-03-03T19:52:16.245028+00:00
response_json:
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draft_name: draft-li-cats-idn
prompt_hash: 862453bf27df9e1a
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-li-cats-idn]
created_at: 2026-03-03T19:52:16.250239+00:00
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draft_name: draft-li-cats-intellinode-network-scheduling
prompt_hash: b98a7474f674800a
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-li-cats-intellinode-network-scheduling]
created_at: 2026-03-03T19:52:27.581078+00:00
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draft_name: draft-li-cdn-node-selection-enhancement
prompt_hash: 7357a52f2547eb55
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-li-cdn-node-selection-enhancement]
created_at: 2026-03-03T19:52:27.598335+00:00
response_json:
  [{"title": "Dynamic Anycast Route Advertisement", "description": "Mechanism enabling CDN nodes to dynamically advertise or withdraw anycast BGP routes based on real-time server load and link quality metrics.", "type": "mechanism"}, {"title": "Load-Aware BGP Anycast", "description": "Extension to BGP anycast routing that incorporates server load awareness to improve node selection beyond traditional network proximity metrics.", "type": "extension"}, {"title": "QUIC-Based Client Selection Feedback", "description": "Protocol mechanism for CDN clients to report application-level requirements and link quality feedback via QUIC to inform node selection decisions.", "type": "mechanism"}, {"title": "Multi-Metric CDN Selection", "description": "Pattern combining network proximity, server load, and application requirements into unified CDN node selection algorithm.", "type": "pattern"}]


draft_name: draft-li-individual-inip
prompt_hash: 00c2e2faae604087
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-li-individual-inip]
created_at: 2026-03-03T19:52:27.604101+00:00
response_json:
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draft_name: draft-li-iotops-intelligent-security
prompt_hash: 62af35cdf3f2a50e
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-li-iotops-intelligent-security]
created_at: 2026-03-03T19:52:27.610033+00:00
response_json:
  [{"title": "Information-Centric Security Framework", "description": "Architecture for IoT networks built around information-centric networking with integrated security protections at naming, data exchange, and caching layers.", "type": "architecture"}, {"title": "Intelligent Protection Optimization System", "description": "Mechanism analyzing network attack methods to optimize security across naming/parsing, data exchange, and caching without additional infrastructure costs.", "type": "mechanism"}, {"title": "Content Privacy in ICN", "description": "Pattern for achieving data and device privacy protection in information-centric networks through intelligent filtering at multiple protocol layers.", "type": "pattern"}, {"title": "Multi-Layer Attack Mitigation", "description": "Requirement defining security protections needed at naming resolution, data exchange routing, and caching layers for comprehensive IoT defense.", "type": "requirement"}]


draft_name: draft-li-spring-rdma-multicast-over-srv6
prompt_hash: d0e67303dcfa18a8
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-li-spring-rdma-multicast-over-srv6]
created_at: 2026-03-03T19:52:27.615922+00:00
response_json:
  [{"title": "End.MT SRv6 Endpoint Behavior", "description": "New SRv6 endpoint behavior that performs per-receiver RDMA Base Transport Header modifications at multicast tree edges.", "type": "extension"}, {"title": "RDMA Multicast over IPv6", "description": "Protocol mechanism enabling RDMA Reliable Connection traffic to traverse IP multicast trees while maintaining point-to-point Queue Pair semantics.", "type": "mechanism"}, {"title": "Hop-by-Hop ACK/NACK Aggregation", "description": "Protocol specification for aggregating RDMA ACK, NACK, and CNP response messages along the reverse multicast path to reduce feedback traffic.", "type": "protocol"}, {"title": "Multi-Replica Write Distribution", "description": "Architecture pattern for distributing RDMA writes across multiple replicas using SRv6-enabled IP multicast trees.", "type": "pattern"}, {"title": "HPC Collective Communications", "description": "Application requirement for RDMA multicast support in high-performance computing and AI training collective operations.", "type": "requirement"}, {"title": "BTH Header Modification at Edges", "description": "Mechanism for modifying RDMA transport headers per multicast receiver at network edges to enable standard QP semantics over multicast delivery.", "type": "mechanism"}]


draft_name: draft-dunbar-neotec-ac-pe2pe-ucmp-applicability
prompt_hash: 77b170682be56993
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-dunbar-neotec-ac-pe2pe-ucmp-applicability]
created_at: 2026-03-03T19:52:40.172183+00:00
response_json:
  [{"title": "Dynamic Time-Scoped UCMP Policy Enforcement", "description": "Apply IETF YANG models to enforce unequal cost multipath policies with time-bounded activation across distributed edge cloud sites.", "type": "mechanism"}, {"title": "Cloud-Initiated Network Policy Activation", "description": "Enable cloud systems to initiate and control time-bounded network policy activation for dynamic AI inference workload distribution.", "type": "pattern"}, {"title": "Multi-Model YANG Integration for Network Requirements", "description": "Map bandwidth, latency, and availability requirements across AC, TE Topology, SR Policy, and QoS YANG models.", "type": "mechanism"}, {"title": "Periodic High-Volume Data Exchange Support", "description": "Design network policies to support periodic, high-volume data exchanges between geographically dispersed AI inference modules.", "type": "requirement"}, {"title": "AC and PE2PE YANG Model Applicability Assessment", "description": "Evaluate gaps and limitations of current IETF YANG specifications for attachment circuit and PE-to-PE policy enforcement.", "type": "mechanism"}]


draft_name: draft-dunbar-neotec-ac-te-applicability
prompt_hash: 6748ac42f5c09d28
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-dunbar-neotec-ac-te-applicability]
created_at: 2026-03-03T19:52:40.191169+00:00
response_json:
  [{"title": "ACaaS for Dynamic Edge AI Placement", "description": "Apply Attachment Circuit-as-a-Service YANG model to dynamically select optimal edge cloud locations for real-time AI inference.", "type": "mechanism"}, {"title": "TE Topology Model for Edge Network Performance", "description": "Use Traffic Engineering topology YANG model to retrieve end-to-end network performance metrics between street-level cameras and edge compute nodes.", "type": "mechanism"}, {"title": "Service Objective Mapping to YANG Models", "description": "Map network service objectives (bandwidth, latency, reliability) to applicable IETF YANG data models across multiple network segments.", "type": "pattern"}, {"title": "Real-Time AI Inference Network Requirements", "description": "Define and enforce network requirements for real-time AI model inference based on geographically distributed camera inputs.", "type": "requirement"}, {"title": "AC and TE YANG Model Gap Identification", "description": "Identify applicability gaps in current AC and TE YANG models for edge cloud AI use cases.", "type": "mechanism"}]


draft_name: draft-liao-aipref-autoctl-core
prompt_hash: bc34a23392dff1f9
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-liao-aipref-autoctl-core]
created_at: 2026-03-03T19:52:50.242828+00:00
response_json:
  [{"title": "Machine-readable automation permissions format", "description": "Defines a file format for declaring server-side permissions for AI-driven web automation activities.", "type": "protocol"}, {"title": "HTTP method restrictions for automation", "description": "Specifies which HTTP methods (GET, POST, PUT, DELETE, etc.) are permitted for automated access.", "type": "mechanism"}, {"title": "Purpose declaration requirements", "description": "Requires automation agents to declare their intended purpose when requesting access to automated operations.", "type": "requirement"}, {"title": "State-changing activity controls", "description": "Extends automation control beyond read operations to cover a broader range of state-changing server operations.", "type": "extension"}]


draft_name: draft-liao-aipref-autoctl-ext
prompt_hash: 4d62f4c8a03b4e95
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-liao-aipref-autoctl-ext]
created_at: 2026-03-03T19:52:50.260362+00:00
response_json:
  [{"title": "Rate limiting for automation", "description": "Enables service owners to specify rate limits on automated requests based on time windows and request counts.", "type": "extension"}, {"title": "Automation technology restrictions", "description": "Allows service owners to restrict access based on the type or classification of automation technology used.", "type": "mechanism"}, {"title": "API-level permission granularity", "description": "Provides granular control over which specific APIs and endpoints can be accessed by automation systems.", "type": "extension"}, {"title": "Session requirement specifications", "description": "Defines requirements for session establishment, authentication state, and session binding for automated access.", "type": "requirement"}, {"title": "HTML asset annotation mechanism", "description": "Enables marking specific HTML elements and assets with automation permissions metadata.", "type": "mechanism"}]


draft_name: draft-liu-rtgwg-mdt-in-high-bdp
prompt_hash: c34f6236f28339a0
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-liu-rtgwg-mdt-in-high-bdp]
created_at: 2026-03-03T19:52:50.267104+00:00
response_json:
  [{"title": "Massive Data Transmission framework", "description": "Provides an end-to-end architecture for efficient large-scale data transmission utilizing idle network capacity.", "type": "architecture"}, {"title": "Terminal-driven intelligent parameter optimization", "description": "Enables automated adjustment of local system parameters (disk I/O, NIC bandwidth, TCP buffers) based on transmission goals.", "type": "mechanism"}, {"title": "Service identification and traffic statistics", "description": "Mechanisms for classifying data transmission services and collecting relevant traffic statistics.", "type": "mechanism"}, {"title": "Network layer load balancing for MDT", "description": "Load balancing strategies specifically designed for distributing massive data transmission flows across network resources.", "type": "mechanism"}, {"title": "Transmission protocol optimization", "description": "Protocol-level enhancements for improving throughput and efficiency in high bandwidth-delay product networks.", "type": "protocol"}, {"title": "Terminal-network-controller collaboration model", "description": "Defines interaction patterns between client terminals, network devices, and centralized controllers for coordinated transmission.", "type": "architecture"}, {"title": "Same-day/next-day delivery use case requirements", "description": "Specifies functional and performance requirements for enabling same-day or next-day delivery services via off-peak transmission.", "type": "requirement"}]


draft_name: draft-madhavan-aipref-displaybasedpref
prompt_hash: 39f6a9e14720547c
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-madhavan-aipref-displaybasedpref]
created_at: 2026-03-03T19:52:50.274080+00:00
response_json:
  [{"title": "Content usage preference vocabulary", "description": "Defines a standardized vocabulary for expressing permissions and restrictions on content use by search and AI crawlers.", "type": "protocol"}, {"title": "Structured permission declarations", "description": "Enables machine-readable declarations of allowed or prohibited uses of crawled digital content.", "type": "pattern"}, {"title": "Search crawler usage controls", "description": "Specific controls for restricting or permitting use of content collected by search engine crawlers.", "type": "mechanism"}, {"title": "AI crawler usage controls", "description": "Specific controls for restricting or permitting use of content collected by AI training and inference systems.", "type": "mechanism"}]


draft_name: draft-mcp-over-moqt
prompt_hash: ee005fa70096101d
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-mcp-over-moqt]
created_at: 2026-03-03T19:52:50.280232+00:00
response_json:
  [{"title": "MCP message mapping to MOQT objects", "description": "Defines how Model Context Protocol messages are serialized and encapsulated as MOQT objects.", "type": "protocol"}, {"title": "MCP session establishment over MOQT", "description": "Procedures for initiating and negotiating MCP sessions using MOQT as the underlying transport.", "type": "mechanism"}, {"title": "MCP session maintenance over MOQT", "description": "Mechanisms for keeping MCP sessions alive, handling connection state, and recovering from transport failures.", "type": "mechanism"}, {"title": "MOQT publish-subscribe for MCP", "description": "Leverages MOQT's publish-subscribe media delivery semantics to enable efficient MCP message distribution.", "type": "pattern"}, {"title": "Low-latency MCP over QUIC/WebTransport", "description": "Exploits QUIC and WebTransport properties to provide low-latency transport for MCP between language models and external tools.", "type": "extension"}, {"title": "External tool integration via MCP-MOQT", "description": "Enables seamless integration between LLM applications and external data sources/tools through efficient MOQT transport.", "type": "architecture"}]


draft_name: draft-mzhang-nfsv4-recursively-setting
prompt_hash: c08974c2f49534e1
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-mzhang-nfsv4-recursively-setting]
created_at: 2026-03-03T19:52:58.095076+00:00
response_json:
  [{"title": "Recursive Attribute Setting", "description": "Mechanism to set attributes on all files and directories within a parent directory in a single operation.", "type": "mechanism"}, {"title": "Near-Data Computing for NFS", "description": "Apply near-data computing principles to NFSv4 to process data on storage servers and reduce client CPU/memory overhead.", "type": "architecture"}, {"title": "Server-Side Bulk Operations", "description": "Extend NFSv4.2 with server-side bulk attribute modification similar to existing Server-Side Copy mechanism.", "type": "extension"}]


draft_name: draft-pan-aqm-pie
prompt_hash: 38d3e6aa8e979045
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-pan-aqm-pie]
created_at: 2026-03-03T19:52:58.112445+00:00
response_json:
  [{"title": "PIE Queue Management", "description": "Proportional Integral controller Enhanced mechanism for active queue management that controls average queueing latency to a target value.", "type": "mechanism"}, {"title": "Bufferbloat Mitigation", "description": "Active queue management scheme designed to reduce latency and jitter caused by excess network buffers.", "type": "mechanism"}, {"title": "Lightweight Latency Control", "description": "Lightweight queue management design achieving low latency and high link utilization without complex computation.", "type": "mechanism"}]


draft_name: draft-ramadan-mboned-sonar
prompt_hash: e178419b8a91f60e
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-ramadan-mboned-sonar]
created_at: 2026-03-03T19:52:58.126351+00:00
response_json:
  [{"title": "Statistical Multicast Verification", "description": "Protocol combining O(1) IP multicast efficiency with VRF-based unpredictable sampling to verify multicast delivery without trusted intermediaries.", "type": "protocol"}, {"title": "Cryptoeconomic Accountability", "description": "Mechanism using on-chain stake deposits and blockchain attestations to create economic incentives for honest multicast delivery reporting.", "type": "mechanism"}, {"title": "Separated Authentication and Verification", "description": "Pattern separating content authentication via ALTA from coverage verification via statistical sampling to minimize overhead.", "type": "pattern"}, {"title": "Real-Time Multicast Authentication", "description": "ALTA-based authentication scheme providing packet-level authentication with approximately 6% bandwidth overhead.", "type": "extension"}, {"title": "Minimal Coverage Testing Overhead", "description": "Statistical coverage verification mechanism using 320 KB challenge messages per test period and 0.7-2.8 Kbps bandwidth overhead.", "type": "mechanism"}]


draft_name: draft-reilly-sentinel-protocol
prompt_hash: 67d23ab7d06f73f5
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-reilly-sentinel-protocol]
created_at: 2026-03-03T19:52:58.132371+00:00
response_json:
  [{"title": "Sentinel Evidence Package", "description": "Data structure binding payload digests, provenance metadata, signatures, blockchain timestamp proofs, and resolvable identifiers for AI artifacts.", "type": "architecture"}, {"title": "Blockchain-Anchored Integrity", "description": "Protocol using blockchain timestamp proofs to establish tamper-evident, independently verifiable receipts across the AI lifecycle.", "type": "mechanism"}, {"title": "AI Lifecycle Provenance Tracking", "description": "System for recording and verifying provenance across datasets, data transformations, training jobs, checkpoints, fine-tuning, evaluations, and inference.", "type": "architecture"}, {"title": "Transport-Agnostic Serialization", "description": "Protocol design supporting multiple serialization formats (JSON, CBOR) and transport mechanisms for broad interoperability.", "type": "pattern"}, {"title": "IETF Building Blocks Integration", "description": "Protocol leveraging existing IETF standards including COSE/CMS signatures, CBOR (RFC 8949), CDDL (RFC 8610), and NTS-secured time.", "type": "extension"}]


draft_name: draft-romm-aipref-contentsignals
prompt_hash: a7c0a2d8f1f8d52d
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-romm-aipref-contentsignals]
created_at: 2026-03-03T19:53:05.788687+00:00
response_json:
  [{"title": "Content Signal Categories", "description": "Define three nested categories within Automated Processing to express preferences for digital asset usage by automated systems.", "type": "vocabulary"}, {"title": "Preference Expression Framework", "description": "Enable parties to communicate machine-readable preferences about how their digital content can be used in automated processing.", "type": "pattern"}]


draft_name: draft-ruan-spring-priority-flow-control-sid
prompt_hash: 3de5e4bd3d989d4e
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-ruan-spring-priority-flow-control-sid]
created_at: 2026-03-03T19:53:05.804581+00:00
response_json:
  [{"title": "SRv6 Flow Control Extension", "description": "Extend SRv6 with flow control capabilities to enable nodes to signal congestion status in wide area networks.", "type": "extension"}, {"title": "WAN Congestion Notification", "description": "Implement rapid and accurate upstream notification of congestion status in WANs to enable responsive traffic mitigation.", "type": "mechanism"}, {"title": "RDMA-aware WAN Routing", "description": "Support RDMA protocol communication across data centers via SRv6 policies with flow control awareness.", "type": "protocol"}, {"title": "Service-specific SRv6 Policies", "description": "Enable carrying specific services over SRv6 policies to ensure precise handling of priority flows.", "type": "architecture"}]


draft_name: draft-shi-moq-kvcache
prompt_hash: ff5df52df4b79eb5
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-shi-moq-kvcache]
created_at: 2026-03-03T19:53:05.811057+00:00
response_json:
  [{"title": "KVCache Distribution Protocol", "description": "Specify transmission of LLM key-value cache objects over MoQT publish/subscribe transport.", "type": "protocol"}, {"title": "Distributed KVCache Caching", "description": "Enable local nodes to cache KVCache artifacts and retrieve them via subscriptions to reduce bandwidth and recomputation.", "type": "mechanism"}, {"title": "Prefill-Decode Optimization", "description": "Leverage MoQT's publish/subscribe model to share pre-computed KVCache between prefill and decode phases across distributed inference nodes.", "type": "pattern"}, {"title": "Model-Prompt Cache Reuse", "description": "Enable efficient reuse of cached KVCache when same model and prompt are used across multiple inference requests.", "type": "mechanism"}]


draft_name: draft-silver-aipref-vocab-substitutive
prompt_hash: abb19e52b5e54477
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-silver-aipref-vocab-substitutive]
created_at: 2026-03-03T19:53:05.816423+00:00
response_json:
  [{"title": "AI Substitutive Use Category", "description": "Define vocabulary for expressing preferences about post-training uses where AI generates outputs substituting for original digital assets.", "type": "vocabulary"}, {"title": "Inference-time Preference Signals", "description": "Enable asset owners to communicate preferences regarding inference-time AI usage that produces substitute content.", "type": "pattern"}]


draft_name: draft-song-tsvwg-camp
prompt_hash: e914f3f900ea0fb2
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-song-tsvwg-camp]
created_at: 2026-03-03T19:53:18.926911+00:00
response_json:
  [{"title": "Consistency-Aware Multipath Transport", "description": "Transport mechanism that manages multiple network paths while maintaining inter-modal arrival consistency for heterogeneous content streams.", "type": "protocol"}, {"title": "Differentiated Modal Stream Management", "description": "Framework for separating and independently managing different modalities (audio, video, text) across multipath networks.", "type": "mechanism"}, {"title": "Inter-Modal Synchronization", "description": "Coordination mechanism ensuring consistent arrival and playback timing across different content modalities in multipath scenarios.", "type": "mechanism"}, {"title": "Multimodal LLM Transport Optimization", "description": "Transport design specifically optimized for low-latency multimodal content delivery in interactive LLM-based services.", "type": "extension"}]


draft_name: draft-tan-ccamp-uonaco-problem-statement
prompt_hash: e5a06062382751bc
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-tan-ccamp-uonaco-problem-statement]
created_at: 2026-03-03T19:53:18.943036+00:00
response_json:
  [{"title": "Unified Control Plane for Optical Networks and AI Computing", "description": "Integrated orchestration layer that enables optical transport networks and compute schedulers to share real-time state information.", "type": "architecture"}, {"title": "Network-Aware Compute Scheduling", "description": "Compute orchestration system that makes scheduling decisions based on real-time network conditions including latency, bandwidth, and congestion.", "type": "pattern"}, {"title": "Compute-Aware Network Optimization", "description": "Optical network control plane that dynamically adjusts resource allocation based on distributed AI workload requirements.", "type": "pattern"}, {"title": "AIDC Resource Visibility", "description": "Requirement for end-to-end visibility of resources across geographically dispersed AI data centers to optimize distributed training and inference.", "type": "requirement"}]


draft_name: draft-templin-6man-aero3
prompt_hash: e6422654cf8b36f4
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-templin-6man-aero3]
created_at: 2026-03-03T19:53:18.949178+00:00
response_json:
  [{"title": "Overlay Multilink Network Interface (OMNI)", "description": "Virtual link abstraction that enables unified IP internetworking across heterogeneous physical link technologies.", "type": "architecture"}, {"title": "IPv6 ND-Based Network Admission", "description": "Secured network admission mechanism using IPv6 Neighbor Discovery messaging over OMNI virtual links.", "type": "mechanism"}, {"title": "Flow-Based Secure Multilink Path Selection", "description": "Path selection mechanism that chooses among multiple links based on flow characteristics while maintaining security properties.", "type": "mechanism"}, {"title": "Dynamic Neighbor Cache-Driven Route Optimization", "description": "Route optimization achieved through dynamic updates to neighbor discovery caches supporting mobility and multihop operation.", "type": "pattern"}, {"title": "Multicast Forwarding over OMNI", "description": "Multicast forwarding capability natively supported across heterogeneous multilink networks through OMNI abstraction.", "type": "extension"}, {"title": "Multinet Traversal", "description": "Capability enabling seamless traversal and connectivity across multiple interconnected networks with different technologies.", "type": "mechanism"}]


draft_name: draft-templin-intarea-aero
prompt_hash: 106649d8df4bed38
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-templin-intarea-aero]
created_at: 2026-03-03T19:53:18.955076+00:00
response_json:
  [{"title": "IPv6 ULA-Based OMNI Control Plane", "description": "Uses IPv6 unique-local address format for IPv6 Neighbor Discovery messaging to manage OMNI virtual link control plane.", "type": "mechanism"}, {"title": "Router Discovery and Neighbor Coordination", "description": "Protocol mechanism for network admission and management of OMNI link forwarding and routing systems.", "type": "protocol"}, {"title": "Secure Multilink Path Selection", "description": "Selection mechanism for choosing paths across multiple links with integrated security for mobile internetworking.", "type": "mechanism"}, {"title": "Dynamic Neighbor Cache Management", "description": "Real-time neighbor cache updates enabling route optimization, mobility management, and multihop operation.", "type": "pattern"}, {"title": "Multicast Forwarding Support", "description": "Native multicast forwarding capability integrated into AERO/OMNI architecture for mobile networks.", "type": "extension"}]


draft_name: draft-templin-intarea-aero2
prompt_hash: 46e7d47bfe344409
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-templin-intarea-aero2]
created_at: 2026-03-03T19:53:18.962540+00:00
response_json:
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draft_name: draft-thomson-aipref-sup
prompt_hash: faf46a6fb5525307
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-thomson-aipref-sup]
created_at: 2026-03-03T19:53:26.599664+00:00
response_json:
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draft_name: draft-tjw-dbound2-problem-statement
prompt_hash: b7b1e0abea28f527
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-tjw-dbound2-problem-statement]
created_at: 2026-03-03T19:53:26.617280+00:00
response_json:
  [{"title": "DNS-based organizational boundary verification", "description": "Enable confirmation of administrative relationships and organizational boundaries through DNS infrastructure.", "type": "requirement"}, {"title": "Domain boundary inference limitations", "description": "Document current inability of internet clients to reliably determine administrative relationships from domain names alone.", "type": "pattern"}, {"title": "Mitigation strategy assessment", "description": "Analyze shortcomings of existing approaches for establishing domain boundaries and their operational trade-offs.", "type": "pattern"}]


draft_name: draft-traffic-analysis-and-network-mode-mapping
prompt_hash: 4b8e7439df4f3792
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-traffic-analysis-and-network-mode-mapping]
created_at: 2026-03-03T19:53:26.624087+00:00
response_json:
  [{"title": "LLM-based traffic classification framework", "description": "Automate network traffic classification using large language models for feature extraction and pattern recognition.", "type": "architecture"}, {"title": "Multi-modal traffic representation generation", "description": "Generate multi-dimensional feature representations from pcap data for traffic characterization during pre-training phase.", "type": "mechanism"}, {"title": "Dynamic resource allocation mapping", "description": "Formulate resource allocation strategies by mapping classified traffic patterns to computing, storage, and transmission requirements.", "type": "mechanism"}, {"title": "Anomaly detection capability", "description": "Detect network traffic anomalies using LLM-based analysis of traffic patterns and deviations.", "type": "extension"}, {"title": "QoS assurance through traffic mapping", "description": "Ensure Quality of Service by dynamically adjusting resources based on intelligent traffic classification and modality mapping.", "type": "pattern"}, {"title": "Multi-service collaboration support", "description": "Enable coordinated resource allocation across multiple services based on unified traffic analysis and modal mapping.", "type": "pattern"}]


draft_name: draft-tsyrulnikov-rats-attested-inference-receipt
prompt_hash: 0dc6763f757fb7f1
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-tsyrulnikov-rats-attested-inference-receipt]
created_at: 2026-03-03T19:53:26.629743+00:00
response_json:
  [{"title": "COSE_Sign1 envelope for AI inference attestation", "description": "Define a cryptographic envelope structure for signing and verifying confidential AI inference events.", "type": "extension"}, {"title": "CWT claims profile for inference events", "description": "Profile CBOR Web Token claims according to Entity Attestation Token framework for AI inference metadata.", "type": "extension"}, {"title": "Model and input/output binding", "description": "Cryptographically bind model identity and input/output hashes to create tamper-evident inference receipts.", "type": "mechanism"}, {"title": "TEE attestation metadata integration", "description": "Include Trusted Execution Environment platform attestation data in inference receipts for hardware-backed verification.", "type": "extension"}, {"title": "AWS Nitro and Intel TDX support", "description": "Support measurement formats from AWS Nitro Enclaves and Intel TDX with extensible platform architecture.", "type": "protocol"}, {"title": "Inference audit and compliance artifact", "description": "Create a signed artifact suitable for third-party audit and compliance verification of AI inference operations.", "type": "pattern"}]


draft_name: draft-tu-nmrg-blockchain-trusted-protocol
prompt_hash: de5b507d493e77ab
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-tu-nmrg-blockchain-trusted-protocol]
created_at: 2026-03-03T19:53:26.635260+00:00
response_json:
  [{"title": "Blockchain-based trust protocol for 6G", "description": "Define a protocol leveraging blockchain technology to establish and verify trust in sixth-generation intelligent communication networks.", "type": "protocol"}]


draft_name: draft-vaughan-aipref-vocab
prompt_hash: 3a10c1964a5292ef
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-vaughan-aipref-vocab]
created_at: 2026-03-03T19:53:34.905410+00:00
response_json:
  [{"title": "AI Training Content Preference Vocabulary", "description": "A standardized vocabulary for expressing content usage preferences including permissions, usage scope, and data retention.", "type": "mechanism"}, {"title": "Metadata-Based Preference Expression", "description": "A method to embed content preferences directly in metadata for rightsholders to manage AI training usage.", "type": "pattern"}, {"title": "Content-Delivery Protocol Integration", "description": "Integration of preference vocabulary into content-delivery protocols to signal AI training restrictions.", "type": "extension"}, {"title": "Granular Preference Levels", "description": "Support for expressing preferences at multiple levels of granularity from document to collection scope.", "type": "requirement"}, {"title": "Cross-Protocol Interoperability Framework", "description": "A foundation enabling consistent preference expression across diverse Internet protocols.", "type": "architecture"}]


draft_name: draft-wang-cats-innetwork-infer
prompt_hash: 209b562692151c96
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-wang-cats-innetwork-infer]
created_at: 2026-03-03T19:53:34.923394+00:00
response_json:
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draft_name: draft-wang-cats-odsi
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response_json:
  [{"title": "Open Distributed Inference System", "description": "A scalable framework for LLM inference across independent operators without centralized trust requirements.", "type": "architecture"}, {"title": "Execution Dependency Management", "description": "A system for handling sequential dependencies and tight latency constraints in distributed LLM execution.", "type": "mechanism"}, {"title": "Decentralized Inference Coordination", "description": "A coordination protocol for executing inference workloads across mutually untrusted network participants.", "type": "protocol"}]


draft_name: draft-williams-netmod-lm-hierarchy-topology
prompt_hash: 288098a0465b0b90
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-williams-netmod-lm-hierarchy-topology]
created_at: 2026-03-03T19:53:34.944105+00:00
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  [{"title": "Hierarchical Language Model YANG Data Model", "description": "A YANG-based data model defining hierarchical topology for cooperative tiny, small, and large language models.", "type": "protocol"}, {"title": "Multi-Tier LM Coordination Architecture", "description": "A reference architecture for distributed inference, summarization, and decision-making across heterogeneous language models.", "type": "architecture"}, {"title": "Secure Inter-Node Messaging Protocol", "description": "A protocol mechanism for secure message passing between cooperating language model nodes.", "type": "protocol"}, {"title": "Token-Based Authorization Scheme", "description": "An authorization mechanism using tokens for controlling access and operations across hierarchical LM nodes.", "type": "mechanism"}, {"title": "Pluggable Trust Model Framework", "description": "A framework supporting pluggable trust models for decentralized validation across heterogeneous LM deployments.", "type": "extension"}, {"title": "Request Escalation Mechanism", "description": "A mechanism for routing and escalating inference requests through the LM hierarchy based on computational requirements.", "type": "mechanism"}, {"title": "Edge-to-Cloud LM Orchestration", "description": "A standards-based orchestration mechanism for coordinating scalable LM interactions in edge-to-cloud environments.", "type": "architecture"}]


draft_name: draft-xsaopig-nmop-service-flow-modal-mapping
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model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-xsaopig-nmop-service-flow-modal-mapping]
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response_json:
  [{"title": "Service Flow Characteristic Identification", "description": "Mechanism for identifying and classifying service flow characteristics in multi-modal networks.", "type": "mechanism"}, {"title": "ALTO-Based Network State Collection", "description": "Protocol extension using ALTO to collect service flow data and network state information from SDN controllers.", "type": "extension"}, {"title": "SDN Control-Data Plane Separation", "description": "Architecture leveraging SDN to separate control and data planes for intelligent resource mapping.", "type": "architecture"}, {"title": "Flow-to-Modal Resource Mapping", "description": "Mechanism for intelligently mapping service flow characteristics to available network modal resources.", "type": "mechanism"}, {"title": "Multi-Domain SDN Integration", "description": "Architecture for integrating multiple SDN domains to collect diverse network state information.", "type": "architecture"}, {"title": "Dynamic Network Optimization", "description": "Mechanism for continuous optimization of resource allocation based on changing network conditions.", "type": "mechanism"}, {"title": "Provider Information Confidentiality", "description": "Pattern for exposing network state through ALTO while keeping internal provider details confidential.", "type": "pattern"}]


draft_name: draft-xsaopig-nsttlp-traffic-labeling
prompt_hash: f4a98cda592cb724
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-xsaopig-nsttlp-traffic-labeling]
created_at: 2026-03-03T19:53:46.394198+00:00
response_json:
  [{"title": "Service Type Label Embedding", "description": "Protocol mechanism for embedding standardized service type identifiers into network packets.", "type": "mechanism"}, {"title": "Multi-Header Label Support", "description": "Protocol extension supporting service type labels in IPv4/IPv6 headers, MPLS labels, and Ethernet frames.", "type": "extension"}, {"title": "Intelligent Traffic Recognition", "description": "Mechanism enabling network devices to recognize and classify traffic based on embedded service type labels.", "type": "mechanism"}, {"title": "Policy-Based Traffic Forwarding", "description": "Mechanism for making forwarding decisions based on service type labels and associated policies.", "type": "mechanism"}, {"title": "Service-Aware Resource Optimization", "description": "Mechanism for optimizing network resources allocation based on service type information.", "type": "mechanism"}, {"title": "Immersive Media Support", "description": "Extension for supporting high-bandwidth immersive VR services through service type labeling.", "type": "extension"}, {"title": "Real-Time Communication Optimization", "description": "Pattern for optimizing real-time communication services through service type-aware forwarding.", "type": "pattern"}, {"title": "IoT Traffic Differentiation", "description": "Pattern for differentiating and optimizing Internet of Things traffic through service type awareness.", "type": "pattern"}]


draft_name: draft-xu-rtgwg-fare-in-sun
prompt_hash: 90f802af2b2be5c8
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-xu-rtgwg-fare-in-sun]
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  [{"title": "Fully Adaptive Routing Ethernet (FARE)", "description": "Protocol mechanism extending WECMP load-balancing to support dynamic multi-path routing in GPU networks.", "type": "mechanism"}, {"title": "Scale-Up Network Adaptation", "description": "Architecture for adapting scale-out network mechanisms to scale-up GPU cluster environments.", "type": "architecture"}, {"title": "MoE Expert Parallelization", "description": "Mechanism for enabling efficient parallelization of Mixture of Experts across multiple GPUs.", "type": "mechanism"}, {"title": "Tensor Parallelization Support", "description": "Mechanism supporting distributed tensor operations across dozens to hundreds of GPUs.", "type": "mechanism"}, {"title": "Ultra-Low Latency Routing", "description": "Pattern for achieving ultra-low latency packet forwarding in AI scale-up networks.", "type": "pattern"}, {"title": "Ultra-High Throughput Fabric", "description": "Requirement for supporting ultra-high-throughput data transmission in GPU-based computing clusters.", "type": "requirement"}, {"title": "Adaptive Load Balancing", "description": "Mechanism for dynamically balancing load across multiple paths in response to network conditions.", "type": "mechanism"}, {"title": "Large Language Model Network Optimization", "description": "Pattern for optimizing network infrastructure specifically for distributed LLM training and inference.", "type": "pattern"}]


draft_name: draft-xu-sidrops-asrank-vulnerabilities
prompt_hash: 901b655453a67ab2
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-xu-sidrops-asrank-vulnerabilities]
created_at: 2026-03-03T19:53:55.203860+00:00
response_json:
  [{"title": "ASRank Sensitivity Analysis", "description": "Quantifies how small changes in BGP routing data can significantly alter AS business relationship inference results.", "type": "pattern"}, {"title": "Adversarial Manipulation Framework", "description": "Demonstrates minimal data manipulation examples that can alter ASRank outputs without detection.", "type": "mechanism"}, {"title": "Structural Vulnerability Identification", "description": "Identifies specific design weaknesses in ASRank's inference algorithm that enable manipulation.", "type": "requirement"}, {"title": "ASRank Robustness Countermeasures", "description": "Proposes security measures to detect or prevent adversarial manipulation of ASRank inference.", "type": "mechanism"}]


draft_name: draft-yang-nmrg-mcp-nm
prompt_hash: d48ef86d020edde0
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-yang-nmrg-mcp-nm]
created_at: 2026-03-03T19:53:55.220517+00:00
response_json:
  [{"title": "MCP Network Management Integration", "description": "Applies Model Context Protocol to refactor network management operations as extensible tools.", "type": "architecture"}, {"title": "MCP Server Discovery for Networks", "description": "Defines mechanisms for discovering multiple MCP servers in network management deployments.", "type": "protocol"}, {"title": "Network Element MCP Communication", "description": "Establishes communication patterns between network elements and controllers using MCP.", "type": "protocol"}, {"title": "AI-Assisted Network Capability Exposure", "description": "Exposes network capabilities and management functions as AI-accessible tools through MCP.", "type": "architecture"}, {"title": "MCP-based Network Gateway Integration", "description": "Defines MCP communication between network elements and centralized gateway controllers.", "type": "extension"}]


draft_name: draft-yang-spring-sr-policy-intelligent-routing
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model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-yang-spring-sr-policy-intelligent-routing]
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  [{"title": "Network Quality-based SR Path Selection", "description": "Selects among multiple SR Policy candidate paths based on real-time network quality metrics.", "type": "mechanism"}, {"title": "Intelligent SR Policy Routing in MPLS", "description": "Implements quality-aware routing decisions for SR policies in MPLS environments.", "type": "extension"}, {"title": "Intelligent SR Policy Routing in IPv6", "description": "Implements quality-aware routing decisions for SR policies in IPv6 SRv6 environments.", "type": "extension"}, {"title": "Dynamic Candidate Path Evaluation", "description": "Continuously evaluates dynamic SR policy candidate paths against network quality indicators.", "type": "mechanism"}, {"title": "Composite SR Path Intelligence", "description": "Applies intelligent selection logic to composite candidate paths combining multiple routing strategies.", "type": "pattern"}]


draft_name: draft-yang-srv6ops-intelligent-routing
prompt_hash: a86e9d693f00f107
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-yang-srv6ops-intelligent-routing]
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response_json:
  [{"title": "Network Quality-based SRv6 Path Selection", "description": "Selects among multiple SRv6 Policy candidate paths based on real-time network quality metrics.", "type": "mechanism"}, {"title": "Intelligent SRv6 Routing in IPv6", "description": "Implements quality-aware source routing decisions for SRv6 policies in IPv6 environments.", "type": "extension"}, {"title": "Dynamic SRv6 Candidate Path Evaluation", "description": "Continuously evaluates dynamic SRv6 policy candidate paths against network quality indicators.", "type": "mechanism"}, {"title": "SRv6 Explicit Path Quality Optimization", "description": "Optimizes explicit SRv6 paths by incorporating network quality metrics into path selection.", "type": "extension"}]


draft_name: draft-yao-tsvwg-cco-requirement-and-analysis
prompt_hash: 9be720de71ef6e1a
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-yao-tsvwg-cco-requirement-and-analysis]
created_at: 2026-03-03T19:53:55.239098+00:00
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  [{"title": "Network-Assisted Collective Communication", "description": "Proposes in-network optimization of collective communication operations for AI training clusters.", "type": "architecture"}, {"title": "RDMA-Compatible Collective Acceleration", "description": "Designs network-assisted collective optimization mechanisms compatible with RDMA transport.", "type": "mechanism"}, {"title": "One-to-Many Collective Optimization", "description": "Reduces bandwidth overhead for broadcast/scatter operations in parallel AI clusters.", "type": "mechanism"}, {"title": "Many-to-One Collective Optimization", "description": "Reduces bandwidth overhead for gather operations in parallel AI clusters.", "type": "mechanism"}, {"title": "Many-to-Many Collective Optimization", "description": "Reduces bandwidth overhead for all-reduce and all-gather operations in parallel AI clusters.", "type": "mechanism"}, {"title": "Collective Communication Gap Analysis", "description": "Identifies requirements gap between network-assisted collective acceleration schemes and RDMA semantics.", "type": "requirement"}, {"title": "AI Cluster Transport Efficiency", "description": "Analyzes optimization opportunities for generative AI workload communication patterns.", "type": "pattern"}]


draft_name: draft-yc-ipv6-for-ioa
prompt_hash: 7a901419b8f06f2d
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-yc-ipv6-for-ioa]
created_at: 2026-03-03T19:54:10.070924+00:00
response_json:
  [{"title": "IPv6 Address Space for Agent Identity", "description": "Leverage IPv6's vast address space to assign unique identities to hundreds of billions of intelligent agents.", "type": "architecture"}, {"title": "Native End-to-End Agent Connectivity", "description": "Enable direct peer-to-peer communication between agents without intermediary translation layers using IPv6's native capabilities.", "type": "architecture"}, {"title": "Agent Discovery via IPv6 Built-in Features", "description": "Utilize IPv6 mechanisms like neighbor discovery and multicast to enable automatic agent discovery and registration.", "type": "mechanism"}, {"title": "Agent Security via IPv6 IPsec Integration", "description": "Apply IPv6's native IPsec support for securing agent-to-agent communications at the network layer.", "type": "extension"}, {"title": "Quality of Service for Agent Traffic", "description": "Define IPv6 traffic class and flow label usage patterns specific to agent workloads and priorities.", "type": "requirement"}, {"title": "IPv6 Extension Headers for Agent Metadata", "description": "Define optional IPv6 extension headers to carry agent-specific metadata and capabilities information.", "type": "extension"}, {"title": "Agent Mobility with IPv6 MIPv6", "description": "Adapt Mobile IPv6 mechanisms to support agent migration across network domains.", "type": "mechanism"}]


draft_name: draft-zeng-mcp-network-measurement
prompt_hash: 88a0c7fd88f52438
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-zeng-mcp-network-measurement]
created_at: 2026-03-03T19:54:10.089001+00:00
response_json:
  [{"title": "MCP Server Model for Network Devices", "description": "Define how network devices expose measurement capabilities as MCP servers with standardized tools and resources.", "type": "architecture"}, {"title": "Natural Language Network Measurement Commands", "description": "Enable AI clients to translate natural language queries into network measurement operations via MCP prompts.", "type": "pattern"}, {"title": "Real-time Performance Monitoring Protocol", "description": "Specify MCP tools for continuous network metrics collection and streaming from device servers.", "type": "protocol"}, {"title": "Intelligent Fault Diagnosis via MCP", "description": "Define MCP resources and tools to enable AI-driven root cause analysis of network faults.", "type": "mechanism"}, {"title": "Automated Topology Discovery Workflow", "description": "Implement MCP-based orchestration for discovering and mapping network topology without manual intervention.", "type": "pattern"}, {"title": "Measurement Data Schema Standardization", "description": "Define standard JSON schemas for network measurement data exchanged via MCP.", "type": "requirement"}, {"title": "MCP Security for Measurement Access Control", "description": "Specify authentication and authorization mechanisms for MCP clients accessing network measurement capabilities.", "type": "extension"}]


draft_name: draft-zeng-mcp-network-mgmt
prompt_hash: 8ae683ff07a5713e
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-zeng-mcp-network-mgmt]
created_at: 2026-03-03T19:54:10.097125+00:00
response_json:
  [{"title": "Network Equipment as MCP Servers", "description": "Define capability tokens and error codes for routers and switches to expose management functions as MCP servers.", "type": "architecture"}, {"title": "MCP Tools for Device Configuration", "description": "Specify standardized MCP tool definitions for common network device configuration operations.", "type": "protocol"}, {"title": "MCP Resources for Device State", "description": "Define MCP resource schemas to represent network device state, inventory, and status information.", "type": "protocol"}, {"title": "MCP Prompts for Network Management Workflows", "description": "Specify prompt templates to guide AI agents through complex network management tasks.", "type": "pattern"}, {"title": "Backward Compatibility with Existing MCP", "description": "Ensure network management extensions do not break existing MCP implementations through versioning.", "type": "requirement"}, {"title": "Device-Specific Error Code Extensions", "description": "Define additional error codes to represent network equipment-specific failure conditions.", "type": "extension"}, {"title": "Multi-device Management Orchestration", "description": "Provide patterns for MCP clients to coordinate operations across multiple network devices.", "type": "pattern"}]


draft_name: draft-zhang-rtgwg-multicast-requirements-gaps-aidc
prompt_hash: d2689b325eb4a0ff
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-zhang-rtgwg-multicast-requirements-gaps-aidc]
created_at: 2026-03-03T19:54:10.105070+00:00
response_json:
  [{"title": "Point-to-Multipoint Data Distribution for Model Training", "description": "Define multicast requirements for efficiently distributing training data to multiple compute nodes in large language model training.", "type": "requirement"}, {"title": "Low-Latency Multicast for Inference Serving", "description": "Specify multicast mechanisms to distribute inference requests and model updates with minimal latency across data centers.", "type": "requirement"}, {"title": "Bandwidth Optimization via Multicast", "description": "Identify gaps where existing multicast cannot achieve efficiency requirements for AI datacenter point-to-multipoint traffic.", "type": "requirement"}, {"title": "Reliable Multicast for Model Synchronization", "description": "Analyze reliability requirements for multicast in distributed AI training to ensure all nodes receive consistent model updates.", "type": "requirement"}, {"title": "Multi-tenant Multicast Isolation in AIDCs", "description": "Define requirements for isolating multicast groups between different AI workloads and tenants in shared data centers.", "type": "requirement"}, {"title": "Dynamic Multicast Group Management", "description": "Specify requirements for rapid multicast group creation and membership changes to match dynamic AI workload scaling.", "type": "requirement"}, {"title": "Congestion Control for AI Multicast Traffic", "description": "Identify gaps in existing multicast congestion control for handling bursty AI training and inference patterns.", "type": "requirement"}, {"title": "In-network Aggregation for AI Multicast", "description": "Analyze requirements for leveraging in-network compute to aggregate gradients and model updates in multicast trees.", "type": "requirement"}]


draft_name: draft-zhao-anima-automatic-congestion-relief
prompt_hash: 9ec89a38c41ba53d
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-zhao-anima-automatic-congestion-relief]
created_at: 2026-03-03T19:54:10.112696+00:00
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  [{"title": "Intelligent Traffic Analysis for Congestion Detection", "description": "Implement machine learning-based analysis to detect network congestion patterns and anomalies in real-time.", "type": "mechanism"}, {"title": "Dynamic Traffic Regulation", "description": "Define algorithms to automatically adjust traffic routing and rate limiting in response to detected congestion.", "type": "mechanism"}, {"title": "Fiber Failure Self-Healing Response", "description": "Specify automatic rerouting and load balancing mechanisms triggered by fiber optic failures.", "type": "mechanism"}, {"title": "Real-time Congestion Notification", "description": "Design a protocol for network devices to communicate congestion status to enable coordinated relief actions.", "type": "protocol"}, {"title": "Autonomous Network Self-Healing Architecture", "description": "Define an autonomous system architecture where networks detect and remediate congestion without manual intervention.", "type": "architecture"}, {"title": "Congestion Relief Metrics and KPIs", "description": "Establish measurement criteria for evaluating effectiveness of automatic congestion relief mechanisms.", "type": "requirement"}]


draft_name: draft-zhao-detnet-enhanced-use-cases
prompt_hash: 14d6c9ecdb9e253e
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-zhao-detnet-enhanced-use-cases]
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response_json:
  [{"title": "Industrial Internet Deterministic Requirements", "description": "Define network latency, jitter, and reliability constraints specific to industrial automation and control systems.", "type": "requirement"}, {"title": "High Experience Video Requirements", "description": "Specify deterministic networking requirements for low-latency, high-quality video delivery across distributed networks.", "type": "requirement"}, {"title": "Intelligent Computing Resource Allocation", "description": "Establish deterministic network requirements for distributed AI inference and edge computing workloads.", "type": "requirement"}, {"title": "ISAC-enabled Smart Factory Architecture", "description": "Define network requirements for integrated sensing, communication, and control in factory environments.", "type": "architecture"}, {"title": "Cross-domain Property Mapping", "description": "Identify and document common deterministic properties across industrial, video, computing, and ISAC use cases.", "type": "pattern"}]


draft_name: draft-zhu-anima-service-intent
prompt_hash: 7ff3f95607279572
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-zhu-anima-service-intent]
created_at: 2026-03-03T19:54:20.808613+00:00
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  [{"title": "Service Intent Semantic Model", "description": "Define a structured semantic model for expressing service-level objectives spanning network, compute, and storage resources.", "type": "architecture"}, {"title": "Service Intent Format Specification", "description": "Specify a concise serialization format for service intent with identification, versioning, and lifecycle semantics.", "type": "protocol"}, {"title": "Multi-resource Constraint Expression", "description": "Enable expression of constraints across heterogeneous resources (network, compute, storage) in a unified framework.", "type": "mechanism"}, {"title": "Intent Scope Definition", "description": "Define mechanisms for scoping service intent to specific domains, services, or resource types within autonomic networks.", "type": "mechanism"}, {"title": "Service Intent Lifecycle Management", "description": "Establish semantics for service intent provisioning, activation, modification, and deprovisioning.", "type": "pattern"}, {"title": "AI Inference Service Intent Mapping", "description": "Map emerging AI inference service requirements to structured service intent representations.", "type": "extension"}]


draft_name: draft-zm-rtgwg-mcp-network-measurement
prompt_hash: 7357f640b0b79430
model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-zm-rtgwg-mcp-network-measurement]
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draft_name: draft-zw-nmrg-mcp-network-mgmt
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model: claude-haiku-4-5-20251001
request_json: batch-ideas[draft-zw-nmrg-mcp-network-mgmt]
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draft_name: draft-zw-rtgwg-mcp-network-mgmt
prompt_hash: e0b8f360b9daa5a6
model: claude-sonnet-4-20250514
created_at: 2026-03-03T19:54:34.944862+00:00
request_json:
  Extract discrete technical ideas and mechanisms from this IETF draft.
  Return a JSON array. Each element: {"title":"short name","description":"1-2 sentences","type":"mechanism|protocol|pattern|requirement|architecture|extension"}

  draft-zw-rtgwg-mcp-network-mgmt | Model Context Protocol (MCP) Extensions for Network Equipment Management | 18pg
  Abstract: The Model Context Protocol (MCP) provides a JSON-RPC 2.0 framework
     for interaction between AI applications and external context sources.
     This document specifies minimal extensions that allow network
     equipment (routers, switches, etc.) to act as MCP servers while
     controllers act as MCP clients.  New capability tokens, tools,
     resources, prompts, and error codes are defined without breaking
     existing MCP implementations.





  Network Working Group                                            G. Zeng
  Internet-Draft                                                     Q. Wu
  Intended status: Standards Track                                  Huawei
  Expires: 23 April 2026                                   20 October 2025


  Model Context Protocol (MCP) Extensions for Network Equipment Management
                     draft-zw-rtgwg-mcp-network-mgmt-00

  Abstract

     The Model Context Protocol (MCP) provides a JSON-RPC 2.0 framework
     for interaction between AI applications and external context sources.
     This document specifies minimal extensions that allow network
     equipment (routers, switches, etc.) to act as MCP servers while
     controllers act as MCP clients.  New capability tokens, tools,
     resources, prompts, and error codes are defined without breaking
     existing MCP implementations.

  Status of This Memo

     This Internet-Draft is submitted in full conformance with the
     provisions of BCP 78 and BCP 79.

     Internet-Drafts are working documents of the Internet Engineering
     Task Force (IETF).  Note that other groups may also distribute
     working documents as Internet-Drafts.  The list of current Internet-
     Drafts is at https://datatracker.ietf.org/drafts/current/.

     Internet-Drafts are draft documents valid for a maximum of six months
     and may be updated, replaced, or obsoleted by other documents at any
     time.  It is inappropriate to use Internet-Drafts as reference
     material or to cite them other than as "work in progress."

     This Internet-Draft will expire on 23 April 2026.

  Copyright Notice

     Copyright (c) 2025 IETF Trust and the persons identified as the
     document authors.  All rights reserved.











  Zeng & Wu                 Expires 23 April 2026                 [Page 1]


  Internet-Draft                   MCP-NET                    October 2025


     This document is subject to BCP 78 and the IETF Trust's Legal
     Provisions Relating to IETF Documents (https://trustee.ietf.org/
     license-info) in effect on the date of publication of this document.
     Please review these documents carefully, as they describe your rights
     and restrictions with respect to this document.  Code Components
     extracted from this document must include Revised BSD License text as
     described in Section 4.e of the Trust Legal Provisions and are
     provided without warranty as described in the Revised BSD License.

  Table of Contents

     1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
     2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   3
     3.  Capability Advertisement  . . . . . . . . . . . . . . . . . .   3
       3.1.  Rationale for Each Field  . . . . . . . . . . . . . . . .   4
     4.  Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . .   4
     5.  Resources . . . . . . . . . . . . . . . . . . . . . . . . . .   5
       5.1.  Standard URI Templates and MIME Types . . . . . . . . . .   5
       5.2.  Subscription a

  Return 3-8 ideas. Focus on CONCRETE technical contributions, not general statements.
  JSON array only, no fences.

response_json:
  [
    {
      "title": "Network Equipment MCP Server Role",
      "description": "Network equipment (routers, switches) act as MCP servers while controllers act as MCP clients, extending the Model Context Protocol framework to network management scenarios.",
      "type": "architecture"
    },
    {
      "title": "Network-Specific Capability Tokens",
      "description": "New capability advertisement tokens that allow network equipment to declare their MCP server capabilities during the initialization handshake.",
      "type": "extension"
    },
    {
      "title": "Network Management Tools via MCP",
      "description": "Standardized tool definitions that enable network controllers to invoke management operations on network equipment through the MCP tools interface.",
      "type": "mechanism"
    },
    {
      "title": "Network Resources with URI Templates",
      "description": "Standard URI templates and MIME types for accessing network equipment resources like configuration data, operational state, and monitoring information.",
      "type": "pattern"
    },
    {
      "title": "Network Equipment Error Codes",
      "description": "Specialized error codes for network management scenarios that extend the base MCP error handling without breaking existing implementations.",
      "type": "extension"
    }
  ]


