```json
{
  "s": "This draft proposes an authenticated in-band mechanism for DNS operators to securely publish DNSSEC key parameters (CDS/CDNSKEY records) that enables parent registries to cryptographically validate and provision DS records without out-of-band verification. It establishes a preferred DNSSEC bootstrapping method for zones not yet securely delegated.",
  "n": 3,
  "nn": "Incremental improvement on existing DNSSEC enrollment mechanisms (RFC 8078, RFC 7344); introduces authenticated signal approach but builds on established DS/CDS/CDNSKEY concepts rather than fundamentally new architecture.",
  "m": 4,
  "mn": "Well-defined protocol mechanism with clear operational procedures; updates to RFCs indicate mature specification; lacks extensive implementation examples or test vectors for top-tier maturity.",
  "o": 3,
  "on": "Shares core concepts with RFC 8078 and RFC 7344 DNSSEC enrollment work; addresses known limitations in existing approaches but operates within established DNSSEC framework without novel technical departures.",
  "mo": 3,
  "mon": "Active IETF WG collaboration with public GitHub repository indicates ongoing development; single 2024 revision suggests steady but not rapid progression; typical for niche DNS operations topic.",
  "r": 1,
  "rn": "Not relevant to AI/agents; this is purely DNS infrastructure security and DNSSEC key management. No connection to autonomous agents, AI safety, or agent protocols.",
  "c": [
    "Other AI/agent"
  ]
}
```


```json
{
  "s": "Crovia Seal v1 is a cryptographic receipt format for recording provenance of AI-generated outputs through Ed25519-signed JSON containing input/output digests, model metadata, timestamps, and hash chains. The format supports offline verification, transparency log inclusion, and witness co-signatures for tamper-evident attestation.",
  "n": 3,
  "nn": "Applies established cryptographic primitives (Ed25519, SHA-256, hash chains) to a timely problem domain (AI output provenance), but lacks novel cryptographic or protocol innovations; similar to existing supply-chain signing schemes adapted for AI context.",
  "m": 4,
  "mn": "Well-defined protocol specification with explicit canonicalization rules, domain separation, and optional extension fields; appears implementation-ready but lacks test vectors, code examples, or interoperability validation.",
  "o": 3,
  "on": "Shares architectural concepts with X.509/PKI attestation formats and supply-chain provenance systems (SLSA, in-toto); distinct but analogous to emerging AI model card and disclosure standards.",
  "mo": 2,
  "mon": "Single draft from May 2026 with no visible WG sponsorship, related RFCs, or implementation ecosystem; early-stage proposal without demonstrated adoption or community iteration.",
  "r": 5,
  "rn": "Directly addresses critical AI safety and accountability requirement—cryptographic proof of AI system involvement in content generation—essential for agent identity, auditability, and policy enforcement.",
  "c": ["Agent identity/auth", "Data formats/interop", "Policy/governance", "AI safety/alignment"]
}
```


```json
{
  "s": "Addresses authorization information sharing across distributed multi-agent systems spanning multiple administrative domains with different identity providers. Proposes using dynamic identity, interoperable claims, and verifiable credentials to enable secure cross-domain authorization.",
  "n": 2,
  "nn": "Incremental contribution combining existing OAuth/OIDC patterns with agent-specific scenarios; verifiable credentials approach is established elsewhere",
  "m": 2,
  "mn": "Early-stage draft presenting challenges and solution approaches without detailed protocol specification or implementation guidance",
  "o": 4,
  "on": "Significant overlap with existing OAuth2.0/OIDC federation specs, SAML assertions, and W3C verifiable credentials work; limited novel integration",
  "mo": 2,
  "mon": "Single revision dated 2026-02-06 with no evidence of working group adoption or iterative community refinement",
  "r": 4,
  "rn": "Directly relevant to agent systems requiring cross-domain trust and authorization; addresses practical multi-agent deployment challenges",
  "c": ["Agent identity/auth", "A2A protocols", "Data formats/interop", "Policy/governance"]
}
```


```json
{
  "s": "Proposes using Model Context Protocol (MCP) to enable AI-assisted network measurement by treating network devices as MCP servers and controllers/LLMs as clients. Framework aims to provide natural language-driven operations for performance monitoring, fault diagnosis, and topology discovery.",
  "n": 2,
  "nn": "Incremental application of MCP to network operations; combines existing technologies (MCP + network telemetry) without fundamental innovation in either domain.",
  "m": 2,
  "mn": "Early sketch stage with architectural description but lacks protocol specifications, formal message definitions, implementation details, or interoperability examples.",
  "o": 4,
  "on": "Significant overlap with existing NETCONF/YANG management frameworks and emerging AI-agent-for-networking proposals; MCP application to network ops is conceptually straightforward reuse of existing patterns.",
  "mo": 1,
  "mon": "Single draft with 2026 date (likely future-dated); no evidence of WG adoption, prior revisions, or community discussion; appears exploratory rather than actively developed.",
  "r": 4,
  "rn": "Directly relevant to AI agent applications in networking and human-agent interaction for operations, though focuses on instrumental use rather than core agent protocols.",
  "c": ["A2A protocols", "Autonomous netops", "Data formats/interop", "Human-agent interaction", "Agent discovery/reg"]
}
```


```json
{
  "s": "ATP proposes a dedicated application-layer protocol for AI agent traffic, adding agent-native intent methods and identity mechanisms beyond HTTP. It positions itself as a transport-level solution complementary to existing messaging-layer agent protocols like MCP and ACP.",
  "n": 2,
  "nn": "Incremental approach—applies familiar HTTP-like semantics (methods, status codes, headers) to agent-specific use cases rather than introducing fundamentally new abstractions. The core insight (agents need protocol-level identity and intent semantics) is sound but the execution is conventional.",
  "m": 3,
  "mn": "Defined protocol with stated method vocabulary and transport requirements (QUIC/TCP/TLS), but abstract. Missing implementation examples, test vectors, error handling specifics, and deployment guidance that would indicate production readiness.",
  "o": 4,
  "on": "Significant conceptual overlap with MCP (Model Context Protocol) and other A2A frameworks—those already layer intent semantics and identity. The claimed distinction (transport vs. messaging layer) is valid but blurs in practice; MCP over HTTP already solves many stated problems.",
  "m": 2,
  "mn": "Single draft, March 2026 date suggests speculative/future-dated work. No evidence of WG adoption, community discussion, or iterative refinement. Appears early-stage with no revision history visible.",
  "r": 4,
  "rn": "Directly addresses agent traffic differentiation and observability—core concerns in AI ops. Highly relevant to scaling agentic systems, though the framing as a new protocol rather than HTTP extension/profile may limit adoption appeal.",
  "c": [
    "A2A protocols",
    "Agent identity/auth",
    "ML traffic mgmt",
    "Autonomous netops",
    "Agent discovery/reg",
    "Data formats/interop"
  ]
}
```


```json
{
  "s": "This draft proposes an inter-domain architecture for Source Address Validation (SAV) at the AS level, enabling ASes to generate accurate SAV rules by sharing SAV-specific information while maintaining fallback to general information during partial deployment. The architecture focuses on information types and rule generation guidance rather than specific protocol implementations.",
  "n": 2,
  "nn": "Incremental contribution that extends existing SAV concepts to inter-domain scenarios; adds architectural framing and information taxonomy but represents evolutionary rather than paradigm-shifting work in source validation.",
  "m": 3,
  "mn": "Well-defined architectural framework with clear component relationships and information models; lacks implementation details, test vectors, and concrete protocol specifications that would indicate production readiness.",
  "o": 4,
  "on": "Significant overlap with existing SAVNET work and source validation literature; largely synthesizes known SAV principles into an architectural model without substantial novel mechanisms.",
  "mo": 4,
  "mon": "Active WG development with multiple related drafts in SAVNET; clear community interest and iterative refinement suggesting sustained momentum within the standardization process.",
  "r": 1,
  "rn": "Network security and routing validation topic with no connection to AI agents, autonomous systems in the ML sense, or agent-based technologies; false positive for this evaluation framework.",
  "c": ["Other AI/agent"]
}
```


```json
{
  "s": "FADP proposes HTTP 402-based micropayment authentication for autonomous AI agents using on-chain cryptocurrency proofs embedded in headers. It targets sub-dollar AI agent-to-server transactions with nonce-challenge replay protection and optional third-party verification.",
  "n": 2,
  "nn": "Incremental extension of HTTP 402 with cryptocurrency integration; combines existing payment verification patterns with agent use cases rather than introducing novel cryptographic or protocol mechanisms.",
  "m": 3,
  "mn": "Protocol definition is present with header specifications and nonce mechanism, but lacks detailed implementation examples, test vectors, error handling edge cases, and security analysis of payment verification.",
  "o": 4,
  "on": "Significant overlap with existing payment gateways (Stripe, Alchemy), blockchain verification services, and OAuth/token-based auth patterns; HTTP 402 itself is underutilized but not novel; DeFi payment channels already address micropayments.",
  "mo": 1,
  "mon": "Single draft publication dated 2026-04-23 with no visible revision history, community discussion, or implementation adoption signals; no WG sponsorship evident.",
  "r": 3,
  "rn": "Partially relevant to autonomous agents; focuses narrowly on payment authentication rather than broader agent coordination, capability negotiation, or safety concerns; solves a specific economic flow rather than core agent architecture.",
  "c": [
    "A2A protocols",
    "Agent identity/auth",
    "Data formats/interop",
    "Model serving/inference"
  ]
}
```


```json
{
  "s": "Defines three hybrid key agreement mechanisms for TLS 1.3 combining post-quantum KEMs (ML-KEM) with classical elliptic curve Diffie-Hellman to provide cryptographic agility during the transition to post-quantum cryptography. Addresses immediate standardization needs for quantum-safe TLS without abandoning proven ECC security.",
  "n": 2,
  "nn": "Incremental combination of existing standards (ML-KEM, ECDHE); straightforward hybrid construction following established patterns from NIST and IETF guidance.",
  "m": 4,
  "mn": "Well-defined protocol specifications with clear parameter combinations and integration points into TLS 1.3 framework; appears implementation-ready but lacks test vectors and interoperability data.",
  "o": 4,
  "on": "Significant overlap with concurrent IETF efforts (draft-ietf-tls-hybrid-design, RFC 9180 hybrid KEM patterns); similar combinations being standardized by NIST and other WGs.",
  "mo": 3,
  "mon": "Active standardization momentum in post-quantum TLS space; timing aligns with NIST ML-KEM finalization and industry transition pressure, though specific draft revision activity unclear.",
  "r": 1,
  "rn": "Not relevant to AI agents or autonomous systems; purely cryptographic protocol specification for classical TLS infrastructure.",
  "c": ["Other AI/agent"]
}
```


```json
{
  "s": "ADRP defines a dispute resolution protocol for cryptographically-attested agent-to-agent transactions, separating cryptographic proof verification from contractual satisfaction through a bifurcated dispute model with arbitration mandates. The protocol introduces counter-attestation overrides and aims to be FAA Section 2-compliant without statutory changes.",
  "n": 4,
  "nn": "Novel conceptual contribution distinguishing proof validity from intent satisfaction in agentic systems; the counter-attestation override pattern and arbitration mandate chain represent original approaches to dispute resolution in autonomous agent transactions.",
  "m": 2,
  "mn": "Early sketch phase—abstract defines concepts and high-level mechanisms but 35 pages likely lacks detailed state machine diagrams, message formats, test vectors, or implementation guidance needed for protocol maturity.",
  "o": 2,
  "on": "Minor similarities to existing blockchain dispute resolution and smart contract arbitration patterns; approach to agent transaction verification appears relatively distinct from prior work.",
  "mo": 2,
  "mon": "Single draft submission with dependency on companion specs (ATXN, AIVS) still in WIP status; no evidence of WG adoption, implementation, or community feedback yet.",
  "r": 4,
  "rn": "Directly relevant to AI agent coordination and autonomous transaction semantics; addresses critical gap in agent protocol design (proof ≠ satisfaction) but focuses on legal/dispute layer rather than core agent capabilities.",
  "c": [
    "A2A protocols",
    "Policy/governance",
    "Agent identity/auth",
    "Data formats/interop",
    "Human-agent interaction"
  ]
}
```


```json
{
  "s": "ACCP proposes a semantic compression protocol for AI agent communication achieving 60-90% token reduction through compact message formats and context management. Designed as transport-agnostic complement to MCP and A2A protocols, it combines intent ontology with state compression strategies.",
  "n": 2,
  "nn": "Incremental contribution; token compression via encoding is established practice (e.g., protobuf, msgpack). Semantic compression specific to agents is somewhat novel but builds directly on existing compression and ontology concepts.",
  "m": 2,
  "mn": "Early sketch stage. Abstract describes goals and claimed metrics but 23 pages likely insufficient for detailed protocol specification, codec interface implementation details, or test vectors. No indication of reference implementation.",
  "o": 4,
  "on": "Significant overlap with MCP (tool use, context), Protocol Buffers (compression), and semantic web standards (ontology). Claims to 'complement' MCP/A2A but core compression problem is well-explored in distributed systems; positioning relative to existing solutions unclear.",
  "mo": 1,
  "mon": "Single draft revision (2026-04-07 date suggests recent submission). No evidence of WG discussion, multiple iterations, or community adoption. Early-stage with unclear publication timeline.",
  "r": 4,
  "rn": "Directly relevant to AI agent infrastructure. Token efficiency is genuine concern for multi-agent systems at scale. However, relevance depends heavily on whether ACCP solves real deployment bottlenecks vs. academic optimization.",
  "c": [
    "A2A protocols",
    "Data formats/interop",
    "ML traffic mgmt",
    "Agent discovery/reg"
  ]
}
```


```json
{
  "s": "Proposes a 13-point governance framework for AI/LLM-based autonomous network device management systems, establishing safety principles around human authority, harm prevention, bounded autonomy, and escalation. Addresses the gap in industry standards as autonomous AI moves from advisory to closed-loop production operations.",
  "n": 3,
  "nn": "Framework approach is useful but governance principles for autonomous systems are well-established in robotics, safety-critical systems, and recent AI policy work; the network-specific application is incremental rather than fundamentally novel.",
  "m": 3,
  "mn": "Defines governance areas clearly with good principle coverage, but lacks concrete implementation mechanisms, technical controls, enforcement methods, or testable compliance criteria; reads as reference architecture rather than actionable specification.",
  "o": 3,
  "on": "Shares conceptual overlap with NIST AI RMF, CPS safety frameworks, and autonomous systems governance (ISO 26262, DO-178C); governance principles themselves are not new, though network-specific application differentiates somewhat.",
  "mo": 2,
  "mon": "Single draft submission in March 2026 with no evidence of WG sponsorship, prior iterations, or community feedback cycle; unclear if this reflects early-stage work or exploratory submission.",
  "r": 4,
  "rn": "Highly relevant to autonomous netops and AI safety concerns; directly addresses agent autonomy constraints and human oversight, though positioned as governance rather than technical protocol specification.",
  "c": [
    "Policy/governance",
    "Autonomous netops",
    "AI safety/alignment",
    "Human-agent interaction"
  ]
}
```


```json
{
  "s": "Proposes an intent-based management framework for Software-Defined Vehicles that abstracts network, security, and application configuration to enable safe autonomous vehicle communication and infotainment services in ITS environments.",
  "n": 2,
  "nn": "Intent-based management is well-established; applying it to SDVs is incremental rather than introducing novel concepts or mechanisms.",
  "m": 2,
  "mn": "Early-stage framework document with abstract concepts but limited concrete protocol definitions, architecture details, or implementation guidance.",
  "o": 4,
  "on": "Significant overlap with existing intent-based networking (IBN) frameworks, ONAP, and cloud-native vehicle platforms; limited differentiation from prior work.",
  "mo": 1,
  "mon": "Single draft submission with December 2025 expiration; no evidence of active revision cycle, WG engagement, or community interest.",
  "r": 2,
  "rn": "Tangentially related to agent autonomy; focuses on vehicle network management rather than AI agent behavior, decision-making, or coordination protocols.",
  "c": [
    "Autonomous netops",
    "Policy/governance",
    "Data formats/interop"
  ]
}
```


```json
{
  "s": "Defines a tamper-evident audit protocol (PoB) for verifying autonomous AI agent behavior compliance with declared policies through signed receipts, hash chains, and pre-execution policy gates. Addresses the gap between agent execution and auditability in systems where agents perform privileged actions on behalf of humans.",
  "n": 4,
  "nn": "Applying blockchain-style hash chains and signed receipts to AI agent auditability is relatively novel; combining pre-execution policy gates with tamper-evident trails targets a genuine gap, though individual components (audit logs, policy enforcement) are established patterns.",
  "m": 2,
  "mn": "Draft reads as early sketch with abstract concepts (signed receipt format, policy gate contract, cross-agent reference mechanism) but lacks concrete protocol definitions, message schemas, state machine diagrams, or implementation examples needed for a working spec.",
  "o": 3,
  "on": "Shares concepts with existing audit logging (syslog, CEF), policy enforcement frameworks (XACML, OPA), and distributed trust models (blockchain ledgers, signed certificates), but specific combination for AI agents is not widely standardized.",
  "m": 1,
  "mon": "No evidence of WG adoption, multiple revisions, or community discussion; appears to be a solo submission with no indicated iterative development or external feedback cycles.",
  "r": 5,
  "rn": "Directly targets core AI agent governance challenge: post-hoc verification of agent behavior compliance and action authenticity—critical for deployment in regulated/high-stakes domains.",
  "c": [
    "AI safety/alignment",
    "Agent identity/auth",
    "Policy/governance",
    "A2A protocols",
    "Data formats/interop"
  ]
}
```


```json
{
  "s": "Proposes Agent Collaboration Protocols (ACPs) architecture to enable interconnection and secure collaboration among heterogeneous AI agents across registration, authentication, discovery, interaction, and monitoring stages. Aims to establish foundational infrastructure for Internet of Agents (IoA) ecosystems.",
  "n": 2,
  "nn": "Combines existing concepts (service discovery, authentication, registration) applied to agent context; lacks genuinely novel architectural contributions or protocols.",
  "m": 2,
  "mn": "Early-stage conceptual framework with functional component descriptions but no detailed protocol specifications, message formats, or implementation guidance.",
  "o": 4,
  "on": "Significant overlap with existing IETF work on service discovery (mDNS, DNS-SD), identity management (RATS, ZTNA), and IoT protocols; conceptually similar to agent mesh architectures already explored.",
  "mo": 1,
  "mon": "Single draft revision, no evidence of WG adoption or community engagement; appears to be exploratory work without iterative refinement.",
  "r": 4,
  "rn": "Directly addresses emerging need for agent-to-agent protocols and infrastructure, though framing as 'Internet of Agents' may oversell current maturity of autonomous agent ecosystems.",
  "c": [
    "A2A protocols",
    "Agent identity/auth",
    "Agent discovery/reg",
    "Data formats/interop",
    "Policy/governance"
  ]
}
```


```json
{
  "s": "This draft proposes Agent Gateway requirements to improve scalability and security in agent-to-agent communications, identifying gaps in current gateway implementations. It establishes design principles for a new entity type to facilitate agent networking.",
  "n": 2,
  "nn": "Incremental refinement of gateway concepts applied to agent contexts; straightforward extension of existing networking infrastructure ideas without fundamental innovation.",
  "m": 2,
  "mn": "Early-stage requirements document lacking protocol specifications, implementation details, or concrete mechanisms; presents problem statement but minimal technical depth.",
  "o": 4,
  "on": "Significant overlap with existing API gateway, service mesh, and IoT gateway specifications; concepts largely map to established networking patterns adapted for agent terminology.",
  "mo": 1,
  "mon": "Single revision with no evidence of WG adoption, implementation activity, or community engagement; appears exploratory without sustained development trajectory.",
  "r": 2,
  "rn": "Tangentially related to AI agents; primarily addresses networking infrastructure rather than agent behavior, learning, or autonomous decision-making; uses 'agent' as network entity rather than AI-centric definition.",
  "c": [
    "A2A protocols",
    "Agent identity/auth",
    "Autonomous netops",
    "Data formats/interop",
    "Agent discovery/reg"
  ]
}
```


```json
{
  "s": "ADP proposes a standardized protocol for autonomous agents to file, process, and resolve disputes through automated mechanisms with cryptographic proof and auditable outcomes. It addresses AI agent interactions, SLA breaches, and contract enforcement with support for multiple resolution frameworks.",
  "n": 2,
  "nn": "Incremental combination of existing dispute resolution concepts (arbitration, mediation, evidence submission) applied to agent scenarios; core mechanisms not novel but domain application is relatively new.",
  "m": 3,
  "mn": "Defined protocol with specified message formats, transport mechanisms, and procedural components; lacks implementation details, test vectors, and concrete examples of real-world agent dispute scenarios.",
  "o": 4,
  "on": "Significant conceptual overlap with existing dispute resolution standards (ODR, arbitration protocols) and agent communication frameworks; appears to synthesize rather than innovate technically.",
  "mo": 1,
  "mon": "Draft dated 2026-04-16 (future date raises credibility concerns); no evidence of WG adoption, revisions, or community engagement; likely early-stage or speculative work.",
  "r": 4,
  "rn": "Directly relevant to agent-to-agent protocols and autonomous systems coordination; addresses real pain point of dispute handling in multi-agent systems, though applicability depends on adoption of autonomous agents in production.",
  "c": [
    "A2A protocols",
    "Agent identity/auth",
    "Data formats/interop",
    "Policy/governance",
    "Agent discovery/reg"
  ]
}
```


```json
{
  "s": "This draft proposes use cases and requirements for communication protocols enabling measurement agents deployed on network devices. It addresses the need for standardized communication mechanisms for AI/ML-based network measurement and telemetry collection.",
  "n": 2,
  "nn": "Incremental work applying existing agent communication concepts to network measurement; limited technical novelty beyond stating requirements for a new protocol domain.",
  "m": 2,
  "mn": "Early-stage requirement document; presents use cases and high-level requirements but lacks protocol specification, detailed mechanisms, or implementation guidance.",
  "o": 4,
  "on": "Significant overlap with existing IETF work on network telemetry (YANG, NETCONF), agent frameworks (OPSAWG), and measurement protocols; positioning relative to existing standards unclear.",
  "mo": 2,
  "mon": "Single draft revision with limited evidence of working group traction or community engagement; future publication momentum uncertain.",
  "r": 3,
  "rn": "Partially relevant to AI agents in networking; focuses on measurement infrastructure rather than core AI agent capabilities, decision-making, or autonomy.",
  "c": ["Autonomous netops", "Agent discovery/reg", "Data formats/interop", "A2A protocols"],
  "meta": "Draft quality hindered by unclear differentiation from existing telemetry standards and lack of concrete protocol proposal. May benefit from repositioning as requirements analysis for autonomous network operations rather than standalone protocol work."
}
```


```json
{
  "s": "Proposes an experimental 'ai' URI scheme to provide dedicated access for AI resources and autonomous systems, with HTTPS gateways for human-facing applications. Aims to enable native connectivity between robots and AI services while maintaining interoperability.",
  "n": 2,
  "nn": "Straightforward application of URI scheme mechanics to AI domain; lacks technical depth beyond existing URI RFC framework and does not introduce novel addressing or discovery mechanisms.",
  "m": 2,
  "mn": "Early-stage sketch with abstract description; 6 pages insufficient for protocol specification, missing syntax definition, gateway architecture details, security considerations, and implementation guidelines.",
  "o": 4,
  "on": "Significant overlap with existing agent communication frameworks (CoAP, XMPP, custom protocols); URI schemes for specialized domains well-established; HTTPS gateway pattern conventional; minimal differentiation from prior art.",
  "mo": 1,
  "mon": "Single draft submission with no evident revision history, working group discussion, or implementation interest; no clear pathway to standardization or adoption.",
  "r": 3,
  "rn": "Tangentially addresses agent interoperability but lacks focus on core AI challenges like safety, alignment, or intelligent resource negotiation; treats symptoms (URI routing) rather than fundamental agent coordination problems.",
  "c": [
    "A2A protocols",
    "Agent identity/auth",
    "Agent discovery/reg",
    "Data formats/interop",
    "Human-agent interaction"
  ]
}
```


```json
{
  "s": "This draft identifies an architectural gap in Internet resource discovery for geospatial applications (AR, robotics, autonomous systems) where discovery begins from physical location rather than predefined identifiers. It proposes a conceptual architecture for Geospatial Resource Discovery (GRD) but remains at the problem statement level without protocol or implementation details.",
  "n": 2,
  "nn": "Incremental contribution; applies existing discovery patterns to spatial context, though the framing for emerging applications adds some value",
  "m": 1,
  "mn": "Purely informational problem statement and architecture; no protocol definition, data formats, or implementation details provided",
  "o": 3,
  "on": "Shares conceptual overlap with geolocation services, local discovery protocols (mDNS, DNS-SD), and spatial computing frameworks; positions itself as distinct but relationships to existing work unclear",
  "mo": 2,
  "mon": "Single early-stage draft from January 2026; no indication of WG adoption, multiple revisions, or broader community engagement",
  "r": 3,
  "rn": "Partially relevant to AI agents; directly applicable to autonomous systems and robotics agents requiring spatial discovery, but not core to agent protocols or AI safety concerns",
  "c": [
    "Agent discovery/reg",
    "Data formats/interop",
    "Autonomous netops",
    "Other AI/agent"
  ]
}
```


```json
{
  "s": "This draft evaluates how existing IETF YANG data models (AC, TE Topology, SR Policy, QoS) can support dynamic, time-scoped UCMP policies for AI inference workloads distributed across edge cloud sites. It identifies gaps in model expressiveness, policy lifecycle handling, and cloud-network API abstraction needed for real-time coordination.",
  "n": 2,
  "nn": "Incremental contribution applying existing YANG models to a specific use case; the technical approach is straightforward mapping of known models to edge cloud requirements without fundamental methodological innovation.",
  "m": 2,
  "mn": "Early-stage applicability study; identifies problems and gaps but lacks concrete protocol extensions, implementation details, or test vectors demonstrating solutions to the identified limitations.",
  "o": 3,
  "on": "Shares core concepts with existing work on YANG-based network policy management, SR policies, and QoS modeling; some overlap with cloud-network integration efforts but with specific focus on UCMP and time-scoped policies.",
  "mo": 2,
  "mon": "Single revision draft from 2026 with limited indication of WG adoption or community momentum; appears to be exploratory work rather than active standardization effort.",
  "r": 3,
  "rn": "Partially relevant to AI infrastructure; addresses ML workload distribution and network optimization for inference services, but focuses on low-level network policy mechanisms rather than AI agent coordination or decision-making.",
  "c": [
    "ML traffic mgmt",
    "Autonomous netops",
    "Data formats/interop",
    "Policy/governance"
  ]
}
```


```json
{
  "s": "AgentROA proposes a cryptographic policy enforcement framework for AI agent actions, modeled on BGP RPKI, using signed policy envelopes (ROA), per-hop attestations (ARA), and execution receipts (AER) to enforce scope-narrowing authorization across agent delegation chains. It positions enforcement at capability invocation boundaries external to agent execution contexts via a topology-independent 'Border Gateway' model deployable as proxies, service mesh components, or gateways.",
  "n": 2,
  "nn": "Applies established RPKI ROA concepts to agent authorization with incremental adaptation; cryptographic binding and delegation chain semantics are useful but not fundamentally novel.",
  "m": 3,
  "mn": "Establishes architectural model and protocol object schemas with defined enforcement semantics, but lacks implementation details, test vectors, or concrete deployment examples needed for production readiness.",
  "o": 3,
  "on": "Shares policy enforcement and delegation concepts with existing agent frameworks; cryptographic receipts resemble audit logging; overlaps partially with MCP server governance discussions but addresses a specific niche.",
  "mo": 1,
  "mon": "Single dated draft (2026-04-16) with no evidence of WG adoption, community discussion, or revision history; appears to be initial submission without momentum signals.",
  "r": 4,
  "rn": "Directly addresses AI agent authorization and governance, core concerns for agent deployment; however, assumes specific threat models (agent influence on enforcement) that may not generalize across all use cases.",
  "c": [
    "Agent identity/auth",
    "Policy/governance",
    "A2A protocols",
    "AI safety/alignment"
  ]
}
```


```json
{
  "s": "MCPS proposes a cryptographic security layer for MCP using ECDSA P-256 signatures, agent identity verification, and replay protection without modifying core protocol. The design is backward-compatible and negotiates security through progressive trust levels L0-L4.",
  "n": 2,
  "nn": "Incremental contribution applying established cryptographic patterns (ECDSA, JCS canonicalization) to MCP. Core concepts (message signing, identity verification, replay protection) are well-trodden; novelty limited to domain-specific envelope design.",
  "m": 4,
  "mn": "Detailed specification with four well-defined primitives, explicit trust level progression, canonical encoding choices (RFC 8785, RFC 7518), and self-hostable Trust Authority. Missing test vectors and reference implementation code for full readiness.",
  "o": 3,
  "on": "Shares conceptual overlap with JOSE/JWS (message signing), PKIX identity binding, and nonce-based replay protection schemes. However, MCP-specific envelope framing and progressive trust negotiation provide modest differentiation from generic TLS/mTLS alternatives.",
  "m": 2,
  "mon": "Single draft revision (2026-03-14), no indication of WG adoption or community feedback. MCP itself is Anthropic-proprietary; unclear if IETF standardization path has institutional backing or will attract cross-organizational interest.",
  "r": 4,
  "rn": "Directly relevant to AI agent security. Addresses real threat model (tool tampering, replay, identity spoofing) for agent-to-service communication. Core relevance to agent identity/auth and interoperability, though assumes MCP adoption trajectory.",
  "c": [
    "A2A protocols",
    "Agent identity/auth",
    "Data formats/interop",
    "AI safety/alignment"
  ]
}
```


```json
{
  "s": "DVS defines a lightweight protocol for AI agents to discover and verify skill definitions (task instructions) served over HTTPS, deriving trust entirely from URL origin and TLS rather than centralized registries. Skills are verified if their URLs match a declared Trust Root prefix, leveraging existing DNS/TLS infrastructure for backward compatibility.",
  "n": 2,
  "nn": "Incremental contribution applying existing web trust models (domain ownership via DNS/TLS) to AI agent skill distribution; conceptually straightforward but addresses a practical coordination problem.",
  "m": 3,
  "mn": "Defined protocol mechanism with clear trust model and path-scoping rules, but limited evidence of implementation details, validation logic, or error handling specifications in 12-page draft.",
  "o": 3,
  "on": "Shares trust-by-URL-origin concept with package management (npm, PyPI) and general web security models; related to agent capability discovery standards but no direct standard overlap identified.",
  "mo": 1,
  "mon": "Single draft from March 2026 with no evident revision history, WG sponsorship, or community adoption signals; appears exploratory stage.",
  "r": 4,
  "rn": "Directly addresses AI agent skill discovery and execution, core to agent orchestration and capability management, though framed narrowly around SKILL.md format rather than broader agent coordination.",
  "c": ["Agent discovery/reg", "Agent identity/auth", "Data formats/interop", "A2A protocols"]
}
```


```json
{
  "s": "Analyzes security threats in intent-based request systems where user goals are translated into executable directives across multiple agents and endpoints. Proposes a reference model addressing constraint validation, privilege escalation, tampering, and intent drift without targeting specific domains.",
  "n": 3,
  "nn": "Incremental contribution—applies established security threat modeling to emerging intent-based architectures; core concepts (tampering, privilege escalation, chain-of-custody) are well-known but domain application is useful.",
  "m": 2,
  "mn": "Early sketch phase—presents threat taxonomy and security requirements but lacks concrete protocol specifications, implementation guidance, or detailed validation mechanisms; reference model is conceptual.",
  "o": 3,
  "on": "Moderate overlap with intent-driven system design literature and general multi-hop authorization frameworks; shares threat categories with existing security analyses of autonomous systems.",
  "m": 2,
  "mon": "Limited momentum—single draft revision, April 2026 date suggests early stage; no evident WG adoption or community discussion; solution-agnostic framing may limit traction.",
  "r": 4,
  "rn": "Directly relevant to AI agent security; addresses core risks in agentic systems but positioned as horizontal framework rather than AI-specific—applies broadly to intent platforms.",
  "c": ["Agent identity/auth", "AI safety/alignment", "Policy/governance", "A2A protocols"]
}
```


```json
{
  "s": "WoA proposes a minimal JSON-based format for HTTP hosts to advertise AI agents and enable uniform client invocation, using JSON Schema for input/output description. It serves as a host-level primitive for higher-level discovery systems rather than defining discovery itself.",
  "n": 2,
  "nn": "Incremental contribution combining existing concepts (JSON Schema, .well-known URIs, REST conventions) without substantial technical innovation.",
  "m": 3,
  "mn": "Defined protocol with clear structure and examples, but lacks implementation details, test vectors, error handling specifications, and security considerations depth.",
  "o": 4,
  "on": "Significant overlap with OpenAPI/Swagger (schema definition), ActivityPub (agent advertisement), and emerging agent protocol work (MASAI, OpenAI Agents); limited differentiation in scope.",
  "mo": 1,
  "mon": "Single revision as of submission date; no evidence of WG adoption, implementation ecosystem, or active community feedback cycle.",
  "r": 4,
  "rn": "Directly addresses agent interoperability and invocation, core to AI agent infrastructure, though framed more as operational tooling than agent capability specification.",
  "c": [
    "A2A protocols",
    "Agent discovery/reg",
    "Data formats/interop",
    "Model serving/inference",
    "Agent identity/auth"
  ]
}
```


```json
{
  "s": "Defines performance benchmarking profiles for LLM serving systems by binding terminology and methodology to concrete architectural roles and workload patterns. Provides standardized SUT boundaries and measurement points for reproducible LLM benchmarking without defining new metrics or workloads.",
  "n": 2,
  "nn": "Incremental work applying existing benchmarking frameworks (from companion drafts) to LLM domain; profiles are formalization of common sense architectural roles rather than novel conceptual contribution.",
  "m": 3,
  "mn": "Well-defined profile specifications with clear SUT boundaries and measurement points, but depends on external terminology/methodology drafts (draft-gaikwad-llm-benchmarking-terminology/methodology) that would need concurrent maturity; no test vectors or validation examples provided.",
  "o": 4,
  "on": "Significant overlap with existing LLM benchmarking literature (MLCommons, HELM) and general benchmarking profile patterns; unclear what differentiates IETF profiles from industry standards beyond naming conventions.",
  "m": 2,
  "mon": "Single draft revision in series; unclear WG consensus or broader community adoption; LLM benchmarking not core IETF mission, limiting institutional momentum.",
  "r": 3,
  "rn": "Directly relevant to model serving infrastructure but peripheral to core agent protocol/behavior topics; benchmarking is operational concern rather than fundamental agent capability.",
  "c": ["Model serving/inference", "Data formats/interop", "Other AI/agent"]
}
```


```json
{
  "s": "FAST proposes a protocol using IPv6 Hop-by-Hop options to carry firewall and service tickets, allowing hosts to signal network nodes for admission and service requests. Tickets serve dual purposes: granting traversal rights and indicating desired network services.",
  "n": 2,
  "nn": "Incremental approach combining existing firewall concepts with service signaling; ticket-based mechanisms are not novel, though IPv6 Hop-by-Hop encapsulation is a reasonable choice.",
  "m": 3,
  "mn": "Defined protocol mechanism with ticket semantics described, but lacks implementation details, test vectors, and deployment guidance needed for full specification readiness.",
  "o": 4,
  "on": "Significant overlap with policy-based routing, QoS signaling mechanisms, and existing authorization protocols; conceptually similar to capability-based security and service negotiation in SDN contexts.",
  "mo": 1,
  "mon": "Single draft revision from April 2024 with no apparent WG sponsorship, community discussion, or implementation efforts evident; lacks adoption indicators.",
  "r": 1,
  "rn": "Not relevant to AI/agents; addresses generic network firewall and service admission signaling without connection to autonomous agents, ML systems, or AI applications.",
  "c": ["Other AI/agent"]
}
```


```json
{
  "s": "Defines a management architecture for Delay-Tolerant Networks that operates asynchronously over the Bundle Protocol, enabling autonomous control and minimal footprint for constrained devices in challenged environments with long propagation delays and frequent disruptions.",
  "n": 2,
  "nn": "Incremental advancement tailoring existing management principles to DTN constraints; the architectural patterns (asynchronous, autonomous, lightweight) are established concepts applied to a specific transport protocol.",
  "m": 4,
  "mn": "Detailed specification with architectural definitions, operational models, and protocol requirements; appears implementation-ready with clear design patterns though test vectors not explicitly mentioned in abstract.",
  "o": 2,
  "on": "Minor similarities to existing constrained network management (CoAP, SNMP variations) but novel application to DTN Bundle Protocol's specific characteristics and unidirectional link constraints.",
  "mo": 4,
  "mon": "IETF WG document with active development cycle; DTN is established interest area with ongoing standardization efforts suggesting sustained community momentum.",
  "r": 1,
  "rn": "Not relevant to AI agents or autonomous AI systems; focuses on network device management in challenged environments, orthogonal to AI/ML agent architectures and behaviors.",
  "c": ["Other AI/agent"]
}
```


```json
{
  "s": "This draft identifies networking challenges specific to AI/LLM workloads in federated multi-datacenter deployments, addressing the unique communication patterns and bandwidth requirements of large language model training and inference. It establishes a problem statement for how service providers should coordinate AI services across datacenters given the distinctive characteristics of AI traffic.",
  "n": 2,
  "nn": "Identifying AI traffic as a distinct networking problem is somewhat incremental; prior work has discussed distributed training and inference challenges, though systematic problem framing for inter-DC AI scenarios is useful.",
  "m": 1,
  "mn": "This is explicitly a problem statement draft with no protocol specification, mechanisms, or implementation details—early stage with focus on characterizing the problem space.",
  "o": 3,
  "on": "Shares conceptual overlap with existing IETF work on datacenter networking, ML systems optimization, and distributed training frameworks, but framed specifically for federated service provider scenarios.",
  "mo": 2,
  "mon": "Single revision timestamp (2025-10-13) suggests early draft status; no evidence of WG adoption or multiple iterations driving momentum.",
  "r": 4,
  "rn": "Directly relevant to AI workload networking requirements and federated deployment models, though primarily a problem statement rather than proposing agent protocols or AI safety mechanisms.",
  "c": ["ML traffic mgmt", "Model serving/inference", "Policy/governance", "Data formats/interop"]
}
```


```json
{
  "s": "Proposes EDHOC-AKA, combining AKA authentication with EDHOC key exchange using symmetric cryptography for resource-constrained mobile networks like NTN. Aims to improve authentication efficiency while maintaining mutual authentication and key derivation security.",
  "n": 2,
  "nn": "Incremental combination of existing protocols (AKA + EDHOC); lacks novel cryptographic or architectural contributions.",
  "m": 2,
  "mn": "Early sketch with abstract concepts; no detailed protocol specification, message flows, formal analysis, or implementation guidance provided.",
  "o": 4,
  "on": "Significant overlap with standard 3GPP AKA and EDHOC specifications; the integration appears straightforward without substantial differentiation.",
  "mo": 1,
  "mon": "Single revision, no evidence of WG engagement, community discussion, or adoption pathway.",
  "r": 2,
  "rn": "Tangentially related via agent authentication/identity; focuses on mobile network protocols rather than AI agent systems, frameworks, or autonomous operations.",
  "c": ["Agent identity/auth", "Other AI/agent"]
}
```


```json
{
  "s": "This draft proposes using MOQT (Media over QUIC Transport) as a transport layer for MCP (Model Context Protocol), enabling low-latency publish-subscribe delivery of MCP messages between language model applications and external tools/data sources. It maps MCP protocol semantics onto MOQT objects and defines session establishment procedures.",
  "n": 2,
  "nn": "Incremental combination of two existing protocols; the core contribution is straightforward message mapping without fundamental architectural innovation.",
  "m": 3,
  "mn": "Defines protocol mapping and session procedures, but appears to lack implementation details, test vectors, error handling edge cases, and validation against real-world deployment scenarios.",
  "o": 3,
  "on": "Shares core concepts with existing protocol bridging/tunneling work; overlaps with generic QUIC-based transport specifications, but MCP+MOQT combination is relatively specific.",
  "mo": 2,
  "mon": "Single revision noted (2025-10-20); no evidence of WG adoption, multiple revisions, or significant community engagement; appears early-stage.",
  "r": 4,
  "rn": "Directly relevant to AI agent infrastructure; addresses agent-to-tool communication patterns and data source integration, core MCP use cases.",
  "c": [
    "A2A protocols",
    "Data formats/interop",
    "Model serving/inference",
    "Agent discovery/reg"
  ]
}
```


```json
{
  "s": "Defines a CDDL-based data format for recording and verifying autonomous agent conversations with COSE signatures, enabling accountability and compliance through structured capture of messages, tool invocations, and reasoning traces compatible with SCITT and RFC 9334 Evidence.",
  "n": 3,
  "nn": "Useful contribution combining existing standards (CDDL, COSE, SCITT) for agent auditability; incremental rather than novel given prior work on conversation logging and cryptographic signing.",
  "m": 4,
  "mn": "Well-defined protocol specification with CDDL schema and dual JSON/CBOR representations; appears implementation-ready with clear interoperability requirements, though test vectors and reference implementations not evident from abstract.",
  "o": 3,
  "on": "Moderate overlap with agent telemetry formats and SCITT transparency services; related to conversation logging standards but specific focus on verifiability and agent accountability is somewhat differentiated.",
  "mo": 2,
  "mon": "Single dated revision (2026-05) suggests early-stage draft; no clear evidence of WG adoption, community feedback cycles, or multiple implementation attempts yet.",
  "r": 4,
  "rn": "Directly relevant to autonomous agent governance, auditability, and human oversight—core concerns as LLM agents handle consequential tasks; strong alignment with emerging accountability requirements.",
  "c": [
    "Data formats/interop",
    "Agent identity/auth",
    "Policy/governance",
    "Human-agent interaction",
    "A2A protocols"
  ]
}
```


```json
{
  "s": "Proposes applying the APN (Application-aware Networking) framework to enable fine-grained network services for interactions between AI agents deployed across different clouds and regions. Addresses the need for differentiated network support based on varying task requirements of agent-to-agent communications.",
  "n": 2,
  "nn": "Incremental application of existing APN framework to an emerging use case; the core concept is straightforward extension of known technology to IoA scenarios without fundamental technical innovation.",
  "m": 2,
  "mn": "Early-stage draft presenting problem motivation and framework applicability analysis; lacks detailed protocol specifications, deployment models, or implementation guidance for the proposed APN-IoA integration.",
  "o": 4,
  "on": "Significant overlap with existing APN specifications and general intent-based networking concepts; the IoA application is relatively narrow and the draft does not differentiate substantially from prior APN work.",
  "mo": 1,
  "mon": "First revision with no apparent community discussion or WG engagement; limited indication of adoption interest or continued development momentum in the IETF routing or AI communities.",
  "r": 3,
  "rn": "Partially relevant to AI agent networking; addresses agent-to-agent communication infrastructure needs but focuses narrowly on QoS/traffic differentiation rather than core agent capabilities, safety, or interoperability challenges.",
  "c": [
    "ML traffic mgmt",
    "A2A protocols",
    "Autonomous netops",
    "Data formats/interop"
  ]
}
```


```json
{
  "s": "ELA extends EDHOC with a lightweight authorization mechanism for zero-touch onboarding of constrained devices using ephemeral Diffie-Hellman key exchange. The protocol leverages EDHOC's extension points to enable enrollment authorization in resource-limited IoT/constrained network scenarios with pre-installed trust anchors.",
  "n": 2,
  "nn": "Incremental extension building on established EDHOC foundation; applies existing mechanisms to authorization problem rather than introducing novel cryptographic or protocol concepts.",
  "m": 4,
  "mn": "Well-defined protocol specification with detailed procedures, parameter definitions, and integration with COSE/EDHOC standards; suitable for implementation with clear normative requirements.",
  "o": 3,
  "on": "Shares conceptual overlap with OAuth 2.0 device flows, FIDO device onboarding, and other IoT provisioning standards; distinct in leveraging EDHOC but addresses similar enrollment authorization patterns.",
  "mo": 4,
  "mon": "Active LAKE WG effort (March 2026 revision date suggests recent development); EDHOC momentum provides foundation; clear IoT/constrained device market demand.",
  "r": 1,
  "rn": "Not relevant to AI agents; addresses IoT device onboarding and network authorization. No connection to autonomous agents, AI safety, model serving, or agent-related protocols.",
  "c": ["Other AI/agent"]
}
```


```json
{
  "s": "MARC proposes a vendor-neutral control and uncertainty-disclosure profile for generative models and agentic systems, defining interoperable metadata for confidence reporting and bounded action sets (answering, clarification, retrieval, tool use, deliberation, abstention, escalation). It focuses on externally observable semantics rather than model internals, targeting reduction of silent failures and improved auditability across orchestration layers and user-facing systems.",
  "n": 3,
  "nn": "Useful contribution addressing a real gap in uncertainty communication for AI systems, but builds on established concepts (confidence scoring, action taxonomies) without fundamental novelty; incremental synthesis of existing ideas into a coordination profile.",
  "m": 4,
  "mn": "Well-structured specification with clear scope boundaries, defined metadata elements, and primary action set taxonomy. 50 pages suggests substantive technical detail, though without access to full document cannot confirm presence of implementation examples or test vectors.",
  "o": 3,
  "on": "Shares conceptual space with confidence calibration work, agent orchestration protocols, and model card transparency initiatives; distinct from but related to work on AI system accountability and human-AI interaction frameworks.",
  "mo": 2,
  "mon": "Single draft revision noted (2026 date suggests future); no evidence of WG adoption, community testing, or iterative refinement cycle; appears to be exploratory submission rather than active development effort.",
  "r": 4,
  "rn": "Directly addresses core operational needs for deployed agentic systems—uncertainty communication, action control, auditability—making it highly relevant to production AI agent environments and orchestration platforms.",
  "c": [
    "Data formats/interop",
    "Human-agent interaction",
    "Model serving/inference",
    "AI safety/alignment",
    "A2A protocols",
    "Policy/governance"
  ]
}
```


```json
{
  "s": "Specifies how to carry EST (Enrollment over Secure Transport) over CoAP using OSCORE and EDHOC as alternatives to DTLS, with support for CBOR-encoded certificates. This enables certificate provisioning for constrained IoT devices with lighter cryptographic overhead than traditional EST-coaps.",
  "n": 2,
  "nn": "Incremental combination of existing standards (EST, CoAP, OSCORE, EDHOC) rather than fundamentally new approach; applies proven mechanisms to a specific transport scenario.",
  "m": 4,
  "mn": "Detailed protocol specification building on RFC9148 with clear integration points; references implementation-ready components (EDHOC, OSCORE, COSE) though primary draft maturity depends on referenced I-D stability.",
  "o": 4,
  "on": "Significant overlap with EST-coaps (RFC9148) scope; OSCORE+EDHOC combination already established in other constrained CoAP contexts; primarily a substitution exercise rather than novel composition.",
  "mo": 3,
  "mon": "Active WG development as ACE work item with reasonable progression (23 pages, specific target date); appears to be steady incremental work without exceptional community pressure or multiple rapid iterations.",
  "r": 2,
  "rn": "Not AI/agent-related; purely infrastructure/IoT certificate provisioning. Tangentially relevant only if framing constrained device identity/auth as agent prerequisite, but primary focus is networking protocol mechanics.",
  "c": ["Agent identity/auth", "Data formats/interop", "Other AI/agent"]
}
```


```json
{
  "s": "This draft proposes a NETCONF mechanism to trace configuration changes back to their source NMS/controller/orchestrator via external trace IDs. It addresses troubleshooting and closed-loop automation in multi-NMS environments by adding YANG-based tracking of configuration modifications.",
  "n": 2,
  "nn": "Incremental contribution extending NETCONF with tracing capability; the core concept of configuration lineage tracking is straightforward, though the NETCONF-specific instrumentation is useful.",
  "m": 3,
  "mn": "Defined protocol mechanism with YANG module specification; appears to have concrete operational semantics but lacks implementation examples, test vectors, or deployment guidance.",
  "o": 3,
  "on": "Shares conceptual overlap with OpenTracing/distributed tracing (trace ID propagation) and existing NETCONF operations tracking; similar to correlation ID patterns in enterprise systems.",
  "mo": 2,
  "mon": "Single dated revision (2025-11-03); no evidence of multiple iterative improvements or active WG adoption discussion visible in abstract/metadata.",
  "r": 4,
  "rn": "Directly relevant to autonomous networks and self-healing closed-loop automation; trace-to-source mapping is essential for AI-driven network ops troubleshooting and agent accountability.",
  "c": [
    "Autonomous netops",
    "Agent identity/auth",
    "Data formats/interop",
    "Policy/governance",
    "Other AI/agent"
  ]
}
```


```json
{
  "s": "Proposes MACP, an architectural framework and protocol suite for secure multi-agent collaboration across administrative domains, introducing entities like Agent Management Center and Agent Gateway to enable trusted onboarding, capability discovery, and distributed synchronization.",
  "n": 2,
  "nn": "Incremental contribution combining existing concepts (agent management, capability-based discovery, distributed protocols) without substantial architectural innovation beyond standard service-oriented patterns.",
  "m": 2,
  "mn": "Early-stage draft with architectural overview but lacks detailed protocol specifications, message formats, security mechanisms, implementation examples, or test vectors needed for deployment.",
  "o": 4,
  "on": "Significant overlap with existing work: FIPA agent standards, microservice architectures (service discovery, API gateways), Kubernetes-style orchestration, and distributed capability negotiation protocols.",
  "mo": 1,
  "mon": "Single revision with April 2026 date (likely speculative/future-dated); no evidence of community engagement, working group adoption, or iterative development based on feedback.",
  "r": 4,
  "rn": "Directly relevant to AI agent infrastructure; addresses critical multi-agent coordination needs, though framed as general protocol work rather than explicitly scoped to modern LLM-based agents.",
  "c": [
    "A2A protocols",
    "Agent identity/auth",
    "Agent discovery/reg",
    "Policy/governance",
    "Data formats/interop"
  ]
}
```


```json
{
  "s": "APKI extends X.509 PKI with agent-specific certificate extensions, transparency logs, and trust delegation mechanisms to enable verifiable identity and graduated trust for autonomous AI agents performing Internet-scale actions. The work addresses the mismatch between traditional PKI assumptions (human operators, long-lived services) and AI agent characteristics (ephemeral lifecycles, capability constraints, model provenance tracking).",
  "n": 3,
  "nn": "Incremental but well-motivated extension of X.509; the core novelty lies in the specific agent-context extensions (capability constraints, model provenance, delegation chains) rather than fundamental cryptographic innovation. Reasonable engineering response to a genuine gap, but not a paradigm shift.",
  "m": 3,
  "mn": "Defined protocol with extension specifications and URI scheme, but abstract on implementation detail; no test vectors, reference implementations, or deployment guidance evident. Sufficient for WG evaluation but requires substantial development before production use.",
  "o": 3,
  "on": "Moderate overlap with SPIFFE (workload identity), WIMSE (machine identity), and Certificate Transparency (RFC 9162). Positions itself as compatible bridge rather than replacement, which is appropriate but limits distinctiveness. Agent-specific extension layer is novel within PKI context.",
  "m": 2,
  "mon": "Single 2026 revision with no clear WG sponsorship mentioned; appears to be individual submission. Timely topic (AI agents on Internet) but no evidence of active adoption, implementation feedback, or multi-organizational consensus.",
  "r": 4,
  "rn": "Directly relevant to autonomous agent infrastructure; addresses real operational need as agents perform regulated actions (financial transactions, data access). Gaps in existing PKI for agent trust models are genuine, though scope is primarily identity/auth rather than alignment or safety.",
  "c": ["Agent identity/auth", "A2A protocols", "Data formats/interop", "Agent discovery/reg", "Policy/governance", "Autonomous netops"]
}
```


```json
{
  "s": "Proposes a lightweight alternative to ANI called aNI that reuses existing GRASP and BRSKI protocols with domain keying material while eliminating the complex ACP layer, implementing automation agents as application-level software components without requiring forwarding plane changes.",
  "n": 2,
  "nn": "Incremental simplification of existing ANI framework; removes ACP complexity but reuses established protocols (GRASP, BRSKI) and certificate infrastructure with acknowledged trade-offs in security guarantees.",
  "m": 3,
  "mn": "Protocol mechanism appears defined with clear architectural choices, but document length (21 pages) and stated simplifications suggest may lack comprehensive specification detail and implementation guidance typical of production-ready specs.",
  "o": 4,
  "on": "Significant overlap with ANI/GRASP/BRSKI ecosystem; primarily a design variant removing ACP rather than introducing fundamentally new concepts; closely related to existing autonomic networking infrastructure work.",
  "mo": 2,
  "mon": "Single dated revision (2025-10-20); appears to be exploratory proposal without evident WG adoption, implementation pilots, or community engagement signals; positioned as alternative to established ANI path.",
  "r": 2,
  "rn": "Tangentially related to AI agents; focuses on network automation infrastructure and agent communication patterns rather than AI/ML-specific agent topics; relevant to agent identity/authentication and discovery protocols but not core AI agent concerns.",
  "c": [
    "Agent discovery/reg",
    "Agent identity/auth",
    "A2A protocols",
    "Autonomous netops",
    "Policy/governance"
  ]
}
```


```json
{
  "s": "This draft proposes extending RFC 9309 to allow content creators to signal preferences about how their content is used by automated systems through HTTP headers. It aims to provide a mechanism for indicating usage preferences during content acquisition.",
  "n": 2,
  "nn": "Incremental extension to existing standards; the core concept of signaling content preferences is well-established (robots.txt, rel=nofollow), this primarily adds HTTP header mechanisms",
  "m": 2,
  "mn": "Early draft stage with abstract only; lacks protocol details, header definitions, semantics specification, compliance mechanisms, and implementation guidance",
  "o": 4,
  "on": "Significant overlap with existing preference signaling mechanisms (robots.txt, X-Robots-Tag, HTTP Link headers, machine-readable policies); relationship to RFC 9309 and how this differs needs clarification",
  "mo": 1,
  "mon": "Single version as of specified date; no visible WG adoption, community discussion, or revision history indicating active development or interest",
  "r": 4,
  "rn": "Directly relevant to AI agent governance—addresses how creators can communicate content usage boundaries to automated systems, a core AI safety concern",
  "c": [
    "Policy/governance",
    "Data formats/interop",
    "AI safety/alignment",
    "A2A protocols"
  ]
}
```


```json
{
  "s": "This draft proposes a framework enabling collaborative network management between LLM agents and human operators, featuring enhanced telemetry, decision modules, and human-in-the-loop workflows. It aims to integrate AI-driven automation into existing network management systems while maintaining human oversight and interoperability.",
  "n": 2,
  "nn": "Incremental contribution combining existing concepts (LLM agents, network management, human-in-the-loop) without substantial technical novelty in mechanisms or protocols.",
  "m": 2,
  "mn": "Early-stage framework definition lacking detailed protocol specifications, data model formalization, or implementation guidance; appears to be problem framing rather than solution specification.",
  "o": 4,
  "on": "Significant conceptual overlap with emerging AI agent frameworks, network automation standards, and human-AI interaction guidelines; limited differentiation from parallel industry efforts.",
  "mo": 2,
  "mon": "Single submission with no visible WG sponsorship or community discussion; publication date of 2026 suggests speculative or early-stage work with minimal adoption signals.",
  "r": 4,
  "rn": "Directly relevant to AI agent orchestration in network operations; addresses timely intersection of LLMs and network management, though execution appears preliminary.",
  "c": [
    "Autonomous netops",
    "Human-agent interaction",
    "Data formats/interop",
    "Policy/governance",
    "A2A protocols"
  ]
}
```


This draft proposes a framework for enabling AI agents across different domains to collaborate securely through federated identity, trust establishment, and policy harmonization mechanisms. It addresses cross-domain interoperability challenges without requiring centralized control.

Applies established federated identity and trust patterns (SAML, OAuth, mTLS) to AI agents; the conceptual contribution is incremental adaptation of known solutions rather than novel mechanisms.

Early sketch phase with abstract framework description; lacks concrete protocol specifications, implementation details, message formats, or validation mechanisms needed for deployment.

Significant overlap with SPIFFE/SPIRE (workload identity), existing federated IAM standards, and blockchain-based trust frameworks; limited differentiation for AI-specific use cases.

Single revision at publication date (2026-02-11); no evidence of working group adoption, implementation feedback, or iterative refinement typical of active IETF work.

Partially relevant to AI agent ecosystems but frames problem primarily as identity/federation rather than agent-specific challenges (coordination semantics, capability heterogeneity, collaborative reasoning).

Agent identity/auth
Policy/governance
Agent discovery/reg
Data formats/interop
A2A protocols


```json
{
  "s": "AITP proposes a message-framed transport protocol above AIP specifically designed for autonomous AI agent communication, featuring native method invocation, request-response correlation, and flow control semantics rather than traditional byte-stream abstractions. It aims to provide a common substrate for agent-to-agent messaging with association state management and circuit-breaker mechanisms.",
  "n": 2,
  "nn": "The core concept of designing a transport layer around agent invocation rather than byte streams is incremental; similar ideas appear in RPC frameworks (gRPC, SOAP) and message-oriented middleware. The framing and state machine are competent engineering but not fundamentally novel.",
  "m": 4,
  "mn": "At 34 pages, the draft appears specification-complete with defined segment types, state machines, flow control mechanics, and protocol options. Maturity is limited only by apparent lack of reference implementations or interoperability test vectors.",
  "o": 4,
  "on": "Substantial conceptual overlap with gRPC (method-aware framing, streaming), MOQT (association-based multiplexing), and existing RPC transports. The positioning as 'agent-native' differentiates presentation but not fundamental design principles.",
  "m": 1,
  "mon": "No evidence of WG adoption, multiple revisions, or community interest visible. Single dated revision (2026-03-25) with no apparent implementation ecosystem or deployment roadmap suggests nascent/speculative status.",
  "r": 3,
  "rn": "Directly addresses agent communication infrastructure, but relevance is narrowed by dependence on the pre-requisite AIP specification and unclear adoption prospects. Relevant to A2A protocol layer but not core AI safety, model serving, or agent alignment concerns.",
  "c": [
    "A2A protocols",
    "Data formats/interop",
    "Agent discovery/reg"
  ]
}
```


```json
{
  "s": "Proposes an AI-assisted framework for automating network protocol testing with five automation maturity levels (Level 0-5), leveraging LLMs for test case generation, script creation, and iterative refinement. Provides a reference architecture and roadmap for evolving protocol testing practices using emerging AI capabilities.",
  "n": 2,
  "nn": "Incremental application of existing LLM capabilities to protocol testing; maturity level concept borrowed from similar frameworks (CMM, TRL); limited technical novelty beyond combining known approaches.",
  "m": 2,
  "mn": "Early conceptual sketch with framework components identified but lacking implementation details, formal specifications, concrete algorithms, or working prototypes; maturity levels defined descriptively rather than with measurable criteria.",
  "o": 4,
  "on": "Significant overlap with existing work in automated test generation (symbolic execution, fuzzing), AI-assisted software development, and capability maturity models; similar maturity level hierarchies used in DevOps and autonomous systems.",
  "mo": 1,
  "mon": "Single submission to NMRG with no visible revision history or community engagement; no evidence of WG discussion, adoption signals, or follow-up versions in public records.",
  "r": 3,
  "rn": "Partially relevant; applies AI/LLMs to network testing but framework is generic software testing automation rather than agent-centric; does not address agent identity, coordination, or multi-agent scenarios.",
  "c": ["Autonomous netops", "ML traffic mgmt", "Model serving/inference"]
}
```


```json
{
  "s": "This draft presents ECDH-PSI, a privacy-preserving protocol for two participants to compute set intersection using elliptic curve cryptography and the Meadows protocol. Participants can identify common records without revealing their private datasets to each other.",
  "n": 2,
  "nn": "Instantiates existing Meadows protocol with standard curves; straightforward application of known techniques rather than novel algorithmic contribution.",
  "m": 3,
  "mn": "Protocol is clearly defined with concrete instantiation details and hash-to-curve methods, but lacks implementation examples, test vectors, and formal security proofs.",
  "o": 4,
  "on": "Significant overlap with existing PSI literature; ECDH-based PSI has been explored in prior work; main contribution is standardization rather than new approach.",
  "mo": 1,
  "mon": "Single draft submission (2025-08-20); no evidence of WG adoption, revisions, or community discussion; appears to be initial proposal.",
  "r": 2,
  "rn": "Not directly relevant to AI agents; applicable to secure computation and privacy-preserving data sharing in general, but no specific connection to autonomous systems or agent infrastructure.",
  "c": ["Data formats/interop", "Agent identity/auth"]
}
```


```json
{
  "s": "CAMP proposes a consistency-aware multipath transport protocol built on MPQUIC to handle multimodal content transmission for interactive LLM systems, addressing inter-modal arrival time synchronization across network paths. The design separates audio, video, and text streams with differentiated scheduling while coordinating transport and application layers to minimize latency variance.",
  "n": 3,
  "nn": "Incremental contribution combining existing multipath transport (MPQUIC) with application-aware scheduling for a specific use case; the core concept of modality-aware stream separation and consistency scheduling is useful but not conceptually novel.",
  "m": 2,
  "mn": "Early-stage sketch with protocol definition but lacks implementation details, test vectors, and evaluation results; mechanism descriptions are present but insufficient detail for independent implementation or reproduction.",
  "o": 3,
  "on": "Shares foundational concepts with multipath QUIC work and multimedia synchronization literature; minimal direct overlap with existing RFCs but builds incrementally on established transport mechanisms without significant architectural innovation.",
  "mo": 1,
  "mon": "Single draft submission with no visible revision history or WG engagement; lacks indicators of active development, community adoption, or implementation activity within IETF processes.",
  "r": 4,
  "rn": "Directly relevant to AI agent infrastructure, specifically model serving and interactive multimodal LLM systems; addresses networking requirements for real-time human-agent interaction with streaming content.",
  "c": [
    "Model serving/inference",
    "Human-agent interaction",
    "ML traffic mgmt",
    "Data formats/interop"
  ]
}
```


```json
{
  "s": "Proposes a protocol abstraction layer enabling MOQT to serve as a unified transport for inter-agent communication by mapping request-response and streaming patterns onto MOQT's publish-subscribe model, demonstrated with A2A and MCP protocols.",
  "n": 2,
  "nn": "Incremental contribution: applies existing MOQT transport to agent protocols rather than introducing novel abstractions or mechanisms; the mapping concept is straightforward.",
  "m": 2,
  "mn": "Early sketch phase: abstract protocol layer defined but likely lacking implementation details, test vectors, and concrete code examples needed for deployment.",
  "o": 3,
  "on": "Moderate overlap with existing MOQT work and protocol-agnostic transport mapping efforts; bridges known domains (MOQT, A2A, MCP) rather than addressing novel intersection.",
  "m": 2,
  "mon": "Limited momentum: single draft appearance (2026-03), no evidence of WG adoption, implementation, or community engagement; agent transport remains nascent area.",
  "r": 4,
  "rn": "Directly relevant to agent infrastructure and interoperability; addresses practical need for unified transport across emerging agent ecosystems, though not core ML/AI algorithm work.",
  "c": [
    "A2A protocols",
    "Agent discovery/reg",
    "Data formats/interop",
    "ML traffic mgmt"
  ]
}
```


```json
{
  "s": "This draft identifies networking challenges for distributed LLM training and inference across federated datacenters, focusing on the unique traffic characteristics of AI workloads. It argues that understanding AI-specific network requirements is essential for operating LLM services in multi-datacenter environments.",
  "n": 2,
  "nn": "Problem statement for AI traffic characteristics is useful but incremental; the core insight that distributed LLMs have distinct networking needs is relatively straightforward.",
  "m": 1,
  "mn": "Pure problem statement with abstract framing; no specific protocol mechanisms, architecture proposals, or concrete solutions offered.",
  "o": 4,
  "on": "Significant overlap with existing work on datacenter networking, collective communication optimization, and distributed training infrastructure; similar concerns addressed in ML systems literature.",
  "mo": 2,
  "mon": "Single revision (2024-10-07), no clear WG sponsorship evident; appears to be early-stage exploratory work without demonstrated adoption momentum.",
  "r": 4,
  "rn": "Directly relevant to AI infrastructure and agent/model serving contexts; addresses real operational challenges for distributed AI systems.",
  "c": [
    "ML traffic mgmt",
    "Model serving/inference",
    "Autonomous netops",
    "Data formats/interop"
  ]
}
```


```json
{
  "s": "AIGA proposes a tiered governance framework for autonomous AI agents combining immutable kernel architecture, federated authority networks, and economic incentive alignment. The protocol addresses deployment constraints and adversarial scenarios through action-based authorization and multi-layered approval mechanisms for high-risk operations.",
  "n": 2,
  "nn": "Incremental contribution combining established governance concepts (tiered risk, federated authorities, TEE attestation) with agent-specific application; lacks fundamentally novel technical mechanisms.",
  "m": 3,
  "mn": "Protocol is defined with component descriptions but lacks detailed technical specifications, cryptographic parameters, message formats, state machines, and implementation guidelines needed for standardization.",
  "o": 4,
  "on": "Significant overlap with existing work: TEE attestation from TPM/SGX standards, federated governance from DNS/PKI models, economic incentives from blockchain protocols, multi-signature from existing crypto frameworks.",
  "mo": 1,
  "mon": "Single revision only (2026-01-26); no evidence of WG discussion, community feedback, or iterative development; appears to be exploratory draft without engagement momentum.",
  "r": 4,
  "rn": "Directly relevant to AI agent governance and policy frameworks; addresses real deployment concerns but positioned as protocol rather than governance model, creating scope ambiguity for IETF venue.",
  "c": [
    "Policy/governance",
    "Agent identity/auth",
    "AI safety/alignment",
    "Autonomous netops",
    "Human-agent interaction"
  ]
}
```


```json
{
  "s": "Extends RFC7030 EST with a mechanism for servers to signal optimal certificate renewal timing to clients, addressing the inadequacy of fixed 50%-lifetime renewal heuristics for short-lived certificates.",
  "n": 2,
  "nn": "Incremental extension addressing a practical operational problem; the core concept is straightforward (server-provided renewal hint) with limited technical novelty.",
  "m": 3,
  "mn": "Defines a protocol mechanism with clear specification intent, though the draft appears early-stage (7 pages) and likely lacks detailed examples, edge case handling, or implementation guidance.",
  "o": 2,
  "on": "Minor similarities to existing certificate lifecycle management approaches; EST renewal timing is a naturally scoped problem with limited overlap to other standards.",
  "mo": 3,
  "mon": "Active WG development within LAMPS (Lightweight Armored Multi-Protocol Scheme) with recent revision date; standard maturity trajectory suggests ongoing refinement.",
  "r": 1,
  "rn": "Not relevant to AI agents or autonomous systems; this is pure PKI infrastructure for TLS certificate lifecycle management with no agent-related components.",
  "c": ["Agent identity/auth"]
}
```


```json
{
  "s": "Defines Attenuating Authorization Tokens (AATs), a JWT-based credential format for secure delegation in AI agent systems that cryptographically enforces monotonic scope reduction across delegation chains. Extends RFC 9396 with delegation semantics and tool-level argument constraints, enabling offline verification without network contact to root issuer.",
  "n": 3,
  "nn": "Useful contribution combining existing concepts (JWT delegation, capability attenuation, RAR) into a cohesive agent-specific framework, but builds incrementally on well-established patterns in authorization and capability systems.",
  "m": 4,
  "mn": "Well-structured specification with 72 pages suggesting detailed protocol definition, formal semantics, and constraint vocabulary. Likely includes examples and algorithms, though implementation maturity and test vectors unclear from abstract alone.",
  "o": 3,
  "on": "Shares core concepts with capability-based security literature and prior delegation work (ZCAP, macaroons); overlaps with RAR (RFC 9396) by design; some similarity to OAuth token narrowing but applies to agent tool invocation specifically.",
  "m": 2,
  "mon": "Single draft dated 2026-03-17 suggests early stage; no indication of WG adoption, multiple revisions, or community engagement; appears to be initial submission without visible momentum signals.",
  "r": 5,
  "rn": "Directly addresses core AI agent security concern: safe delegation and scope attenuation in multi-agent systems. Tool invocation constraints and chain verification are fundamental to agent autonomy and safety.",
  "c": ["Agent identity/auth", "A2A protocols", "AI safety/alignment", "Data formats/interop", "Policy/governance"]
}
```


```json
{
  "s": "Proposes an architectural framework for task discovery and agent coordination through a multi-layer platform where task owners publish structured tasks and autonomous agents negotiate execution terms. Surveys existing agent discovery approaches (A2A, OASF, ARDP, DNS-AID) and positions the work as complementary rather than replacement.",
  "n": 2,
  "nn": "Incremental contribution combining existing concepts (task cards, layered architecture, agent discovery) without substantial technical innovation; conceptually straightforward application of known patterns to agent coordination.",
  "m": 2,
  "mn": "Early-stage architectural sketch with functional layer definitions but lacks detailed protocol specifications, message formats, negotiation algorithms, or security mechanisms; no implementation examples or test vectors provided.",
  "o": 4,
  "on": "Significant conceptual overlap with survey targets (A2A, OASF, ARDP); core ideas of agent discovery, capability matching, and platform-mediated task posting are well-established; unclear how framework substantially differs from existing broker/marketplace patterns.",
  "mo": 1,
  "mon": "Single draft revision with March 2026 date suggests recent submission; no evidence of WG discussion, community feedback, or iterative refinement; positioned tentatively ('possible ways,' 'potential standardization venues').",
  "r": 4,
  "rn": "Directly addresses agent orchestration and discovery, core concerns in multi-agent AI systems; timing aligns with growing industry interest; however, framing around IETF standardization may be mismatch for application-layer agent frameworks.",
  "c": [
    "Agent discovery/reg",
    "Data formats/interop",
    "A2A protocols",
    "Human-agent interaction",
    "Other AI/agent"
  ]
}
```


```json
{
  "s": "Extends the Model Context Protocol (MCP) to enable network equipment to function as MCP servers, allowing AI controllers to manage routers and switches through a standardized JSON-RPC framework. Defines new capability tokens, tools, resources, prompts, and error codes while maintaining backward compatibility with existing MCP implementations.",
  "n": 2,
  "nn": "Incremental extension applying existing MCP framework to network management domain; lacks novel protocol mechanisms or architectural innovations.",
  "m": 3,
  "mn": "Defines protocol mechanisms with new extensions but appears to lack detailed implementation examples, test vectors, or deployment guidance typical of implementation-ready specs.",
  "o": 3,
  "on": "Shares foundational concepts with NETCONF/YANG and other network management protocols; MCP application to network domain has limited prior art but conceptually overlaps with API gateway and orchestration patterns.",
  "mo": 2,
  "mon": "Single draft revision dated 2026-05-06 with no evident WG adoption, implementation reports, or community feedback suggesting early-stage, limited-traction work.",
  "r": 4,
  "rn": "Directly addresses AI agent-network interaction by enabling autonomous controllers to manage infrastructure; core relevance to autonomous netops and agent-equipment communication.",
  "c": [
    "A2A protocols",
    "Autonomous netops",
    "Agent identity/auth",
    "Data formats/interop",
    "Agent discovery/reg"
  ]
}
```


```json
{
  "s": "Proposes an intent_chain cryptographic claim to track content provenance and transformations across AI agent workflows, complementing actor_chain delegation records. Provides tamper-evident audit trails with Merkle root embedding in OAuth tokens for efficiency while addressing STRIDE threat categories.",
  "n": 2,
  "nn": "Incremental extension applying established cryptographic patterns (Merkle trees, audit logs, claims-based architecture) to AI agent content tracking; core techniques are well-known, application domain is relatively novel but architecturally straightforward.",
  "m": 2,
  "mn": "Early sketch stage; abstract describes intent and threat model but lacks protocol mechanics detail, serialization formats, Merkle construction specifics, and practical implementation considerations for multi-stage pipelines.",
  "o": 3,
  "on": "Shares conceptual overlap with blockchain audit trails, W3C Verifiable Credentials provenance models, and software supply chain SLSA framework; positioning relative to these is unclear; dependency on companion draft creates coupling.",
  "m": 2,
  "mon": "Limited observable momentum; dated future publication (2026-03-18 suggests speculative entry), appears to be individual contribution without visible WG traction, no evidence of adoption or implementation feedback.",
  "r": 4,
  "rn": "Directly relevant to AI agent governance and autonomous system trustworthiness; addresses legitimate need for content provenance in agentic workflows; less relevant to core AI safety/alignment than to operational security/audit.",
  "c": ["Agent identity/auth", "Policy/governance", "A2A protocols", "Data formats/interop"]
}
```


```json
{
  "s": "Proposes protocol mechanisms for networks to recognize and handle multi-modal AI agent traffic with differentiated quality requirements. Addresses the gap between increasing AI agent network usage and current network inability to distinguish diverse transmission characteristics of multi-modal data streams.",
  "n": 2,
  "nn": "Incremental work applying existing QoS/traffic differentiation concepts to AI agent scenarios; lacks technical depth on novel protocol mechanisms beyond problem motivation.",
  "m": 1,
  "mn": "Problem statement and high-level requirements only; no concrete protocol specification, message formats, state machines, or implementation details provided in abstract.",
  "o": 4,
  "on": "Significant overlap with MPLS traffic engineering, DiffServ, 5G network slicing, and emerging work on ML traffic classification (RFC 8799, ALTO extensions); limited differentiation from existing QoS frameworks.",
  "mo": 1,
  "mon": "Single revision at future date (2026-03); no evidence of WG sponsorship, community engagement, or iterative development; appears speculative.",
  "r": 3,
  "rn": "Partially relevant to AI agent networking but framed as network infrastructure concern rather than agent protocol specification; scope confusion between network layer mechanisms and agent-level protocols.",
  "c": [
    "ML traffic mgmt",
    "Data formats/interop",
    "Autonomous netops",
    "Policy/governance"
  ]
}
```


```json
{
  "s": "This draft advocates for considering end-user impacts when standardizing AI preference signaling mechanisms, emphasizing control over data contributions and privacy. It proposes principles for the ai-pref working group rather than defining concrete technical specifications.",
  "n": 2,
  "nn": "Incremental contribution that frames existing concerns (data privacy, user control) within the specific context of AI preference signaling; limited technical novelty.",
  "m": 1,
  "mn": "Problem statement and principles document; lacks protocol definitions, vocabulary specifications, or implementation guidance that would advance maturity.",
  "o": 3,
  "on": "Shares conceptual overlap with broader IETF work on user privacy signaling and data minimization; related to DNT and similar preference mechanisms but narrowly scoped to AI context.",
  "mo": 2,
  "mon": "Single dated revision (2025-11-27) with uncertain WG adoption status; appears to be early input to ai-pref WG rather than iterative development.",
  "r": 4,
  "rn": "Directly relevant to AI agent governance and policy frameworks; addresses legitimate end-user concerns in AI deployment but more governance-focused than protocol-focused.",
  "c": [
    "Policy/governance",
    "Human-agent interaction",
    "AI safety/alignment",
    "Data formats/interop"
  ]
}
```


```json
{
  "s": "This draft specifies how to transport the Model Context Protocol (MCP) over MOQT, leveraging QUIC's low-latency publish-subscribe capabilities for language model applications to communicate with external tools and data sources. It maps MCP messages to MOQT objects and defines session management procedures.",
  "n": 2,
  "nn": "Incremental combination of two existing protocols (MCP + MOQT); primarily an engineering exercise in protocol mapping rather than introducing novel concepts.",
  "m": 3,
  "mn": "Defines the protocol mapping and procedures at a reasonable level of detail, but appears to lack implementation validation, test vectors, or deployment guidance typical of mature transport specifications.",
  "o": 3,
  "on": "Shares conceptual overlap with MCP over HTTP/SSE and other MCP transport bindings; MOQT itself is a separate WG effort, so this represents a relatively straightforward layering without significant architectural novelty.",
  "mo": 2,
  "mon": "Single revision dated April 2026 with no clear WG sponsorship signal or adoption indicators; positioning is narrow (MCP-specific MOQT binding) with unclear community traction.",
  "r": 4,
  "rn": "Directly relevant to AI agent infrastructure by enabling efficient MCP transport for tool calling and data access patterns; addresses real latency and resource constraints in agent deployments.",
  "c": [
    "A2A protocols",
    "Data formats/interop",
    "Model serving/inference",
    "Agent discovery/reg"
  ]
}
```


```json
{
  "s": "This draft proposes MCP extensions enabling network equipment to function as servers for AI controller clients, defining new capability tokens, tools, resources, and error codes. The work aims for backward compatibility with existing MCP implementations while enabling AI-driven network management.",
  "n": 2,
  "nn": "Incremental extension of existing MCP framework to network domain; applies proven JSON-RPC patterns rather than introducing novel concepts.",
  "m": 2,
  "mn": "Early specification stage with abstract scope; lacks detailed protocol mechanics, implementation examples, error handling specifics, or test vectors needed for production deployment.",
  "o": 4,
  "on": "Significant overlap with YANG-based network management standards (RFC 6241/6242), NETCONF, and prior MCP work; represents relatively straightforward domain application rather than architectural innovation.",
  "mo": 1,
  "mon": "Single 7-page draft with October 2025 date; no evidence of WG adoption, multiple revisions, or community feedback cycle typical of progressing IETF work.",
  "r": 4,
  "rn": "Directly relevant to autonomous network operations and agent-controller interaction patterns; addresses legitimate need for standardized AI-equipment communication in netops domain.",
  "c": [
    "A2A protocols",
    "Autonomous netops",
    "Agent discovery/reg",
    "Data formats/interop",
    "Agent identity/auth"
  ]
}
```


```json
{
  "s": "Proposes integrating autonomous AI agents with digital twin technology for network management, extending traditional DTN architectures with intelligent agents at component levels. The work combines AI agents with network digital twins to enable adaptive and autonomous network operations.",
  "n": 2,
  "nn": "Straightforward combination of two existing concepts (AI agents and digital twin networks) without significant algorithmic or architectural innovation; primarily an application proposal rather than methodological advance.",
  "m": 2,
  "mn": "Early sketch stage with abstract concepts; lacks detailed protocol specifications, algorithmic descriptions, implementation details, or concrete examples of how agents interact within the DTN framework.",
  "o": 4,
  "on": "Significant overlap with concurrent work on AI-driven network management, digital twin networking standards (ITU-T), and multi-agent systems in telecom; limited differentiation from existing DTN and AI agent proposals.",
  "mo": 1,
  "mon": "Appears to be initial submission with no evidence of WG discussion, prior revisions, or community engagement; no indication of adoption or iterative development.",
  "r": 4,
  "rn": "Directly addresses AI agents in network contexts and autonomous network operations, core topics for NMRG; relevance is strong despite execution limitations.",
  "c": [
    "Autonomous netops",
    "AI safety/alignment",
    "Agent discovery/reg",
    "Data formats/interop",
    "Policy/governance"
  ]
}
```


```json
{
  "s": "Proposes ODSI, a decentralized framework for distributed LLM inference across untrusted participants with layer-wise execution, deadline awareness, and accountability mechanisms. Addresses architectural challenges of networked LLM serving without specifying concrete protocols.",
  "n": 3,
  "nn": "Useful contribution combining known concepts (distributed ML, decentralized coordination, deadline-aware execution) into a cohesive inference architecture, but incremental relative to existing distributed systems and federated learning literature.",
  "m": 2,
  "mn": "Early framework specification focusing on architecture and design rationale; explicitly defers protocol details, message formats, and state machines to future documents. Lacks implementation, concrete algorithms, or validation.",
  "o": 4,
  "on": "Significant conceptual overlap with federated learning systems, distributed serving platforms (Ray, vLLM), and decentralized coordination frameworks. Layer-wise execution parallels model parallelism and pipeline parallelism in existing systems.",
  "mo": 2,
  "mon": "Single draft revision dated 2026-03-02 with no visible community adoption, working group backing, or prior versions. No indicators of active development or organizational support.",
  "r": 4,
  "rn": "Directly relevant to model serving/inference and distributed AI systems. Addresses real operational challenges in LLM deployment but framed as networking infrastructure problem rather than core AI agent capability.",
  "c": ["Model serving/inference", "ML traffic mgmt", "Autonomous netops", "Agent identity/auth", "Data formats/interop", "Policy/governance"]
}
```


```json
{
  "s": "Proposes a distributed audit architecture for tracking AI agent delegation, intent, and authorization across internet interactions. Addresses the gap in existing audit mechanisms by linking delegation relationships with execution through context propagation and attestation.",
  "n": 3,
  "nn": "Auditing frameworks for agents are underexplored in IETF; the specific focus on delegation chains and intent tracking is a useful contribution, though audit architectures themselves are not novel.",
  "m": 2,
  "mn": "Early-stage draft presenting conceptual architecture without detailed protocol specifications, implementation details, or comprehensive technical mechanisms for distributed audit record generation and propagation.",
  "o": 3,
  "on": "Shares audit/logging concepts with existing security frameworks (SIEM, structured logging) and agent transparency work, but the specific application to AI agent delegation appears moderately novel.",
  "mo": 2,
  "mon": "Single recent revision (May 2026); limited indication of working group activity, implementation interest, or community feedback driving development momentum.",
  "r": 4,
  "rn": "Directly addresses a critical gap in AI agent governance—auditability of autonomous delegation decisions—which is core to agent trustworthiness and emerging policy requirements.",
  "c": [
    "Policy/governance",
    "Agent identity/auth",
    "Data formats/interop",
    "AI safety/alignment",
    "Human-agent interaction"
  ]
}
```


```json
{
  "s": "This draft proposes a new BGP extended community to signal AS_PATH validation states derived from ASPA within autonomous systems, enabling IBGP speakers to apply local routing policies based on upstream provider authorization verification. It addresses intra-domain policy signaling for BGP security validation.",
  "n": 2,
  "nn": "Incremental extension to existing BGP signaling mechanisms; combines ASPA validation with standard extended community encoding without fundamental innovation.",
  "m": 3,
  "mn": "Protocol mechanism is clearly defined with extended community structure, but lacks implementation examples, deployment scenarios, and interoperability guidance expected of mature specs.",
  "o": 3,
  "on": "Shares conceptual overlap with ASPA (RFC 6811), BGP communities (RFC 1997), and related SIDR validation signaling work; extends rather than duplicates existing standards.",
  "mo": 1,
  "mon": "Single draft revision in 2024 with no evidence of WG discussion, implementation reports, or successive updates indicating active community development.",
  "r": 1,
  "rn": "Not relevant to AI agents or autonomous systems in the machine learning sense; pure network routing infrastructure document unrelated to AI/ML topics.",
  "c": [
    "Data formats/interop",
    "Policy/governance",
    "Other AI/agent"
  ]
}
```


```json
{
  "s": "Proposes DN-ANR, a DNS-based naming and resolution system for AI agents that uses FQDNs as stable identifiers and resolves them to cryptographically-verified endpoints with protocol information. The draft intentionally keeps DNS lightweight by avoiding semantic metadata, delegating discovery and routing decisions to higher layers.",
  "n": 2,
  "nn": "Incremental extension of DNS for a new use case (AI agents); core mechanisms (DNSSEC, FQDN resolution) are established practices applied to agent identity rather than fundamentally novel.",
  "m": 3,
  "mn": "Defines a coherent protocol mechanism with three clear goals and apparent DNS record structure, but lacks detailed specification sections, examples, implementation guidance, and test vectors typical of mature IETF drafts.",
  "o": 3,
  "on": "Shares conceptual overlap with service discovery (SRV records, mDNS), DNSSEC-based verification, and existing agent/service naming conventions; somewhat positioned between DNS-SD and custom agent registries.",
  "r": 2,
  "rn": "Single-author draft from 2026 with no visible WG affiliation, discussion thread, or adoption signals; appears exploratory rather than community-driven.",
  "mo": 4,
  "mon": "Directly addresses timely AI agent interoperability and identity challenges; relevance to emerging agent ecosystems suggests potential interest, though current adoption/momentum indicators are absent.",
  "c": [
    "Agent identity/auth",
    "Agent discovery/reg",
    "A2A protocols",
    "Data formats/interop"
  ]
}
```


```json
{
  "s": "Extends the Entity Attestation Token (EAT) standard with new claims to enable secure, verifiable attestation of AI agent capabilities, functional scope, and policy constraints in decentralized environments. Addresses the emerging need for trustworthy capability declarations in autonomous agent systems.",
  "n": 3,
  "nn": "Useful but incremental contribution—applies existing attestation token framework to a new domain (agentic AI) rather than introducing fundamentally new attestation concepts.",
  "m": 2,
  "mn": "Early-stage draft; defines problem space and conceptual extensions but lacks detailed protocol mechanics, claim schemas, serialization examples, and implementation guidance needed for interoperability.",
  "o": 3,
  "on": "Shares core ideas with emerging capability frameworks (IETF RATS, AI governance tokens) and overlaps with parallel work on agent provenance and model cards; positioning relative to these efforts unclear.",
  "mo": 1,
  "mon": "Very limited momentum—single revision, no evidence of WG adoption, community feedback, or implementation efforts; unclear if this addresses real deployment pain points.",
  "r": 4,
  "rn": "Directly relevant to AI agent identity, capability attestation, and trustworthiness in decentralized agent systems; timely given industry interest in verifiable agent properties.",
  "c": [
    "Agent identity/auth",
    "Data formats/interop",
    "Policy/governance",
    "AI safety/alignment",
    "Agent discovery/reg"
  ]
}
```