--- name: agent-protocol-interleave-270286042939 description: Bridge layer connecting the emerging agentic coordination protocol ecosystem (MCP, A2A, ANP, AGNTCY, AITP, LMOS, AAIF) to the plurigrid/asi skill graph. Maps protocol-level identity mechanisms (W3C DID, OAuth 2.1, IPSIE, Entra Agent ID, Agent Cards, passport.gay) into GF(3)-classified skills. The central unsolved problem — no unified identity across MCP+A2A+A2UI — is directly addressed by the bisimulation oracle composition. version: 1.0.0 trit: 0 role: BRIDGE tags: [mcp, a2a, anp, agntcy, aitp, lmos, aaif, linux-foundation, did, oauth, ipsie, interoperability, gf3, interleave] deployed: 2026-02-19 --- # Agent Protocol Ecosystem × ASI Interleave Bridge connecting the 2025-2026 agentic coordination protocol ecosystem to the ASI skill graph. ## Protocol Map (February 2026 State) ``` Linux Foundation Consolidation: AAIF { MCP, goose, AGENTS.md } -- Anthropic/Google/OpenAI/AWS/Microsoft A2A Project { A2A + absorbed ACP } -- Google-led, 50+ partners LF AI&Data { absorbed ACP from IBM } AGNTCY { discovery+messaging+obs } -- Cisco-led, 65+ companies Outside Linux Foundation: ANP { W3C DID + JSON-LD } -- Decentralized open-internet AITP { NEAR accounts + payments } -- NEAR Foundation UCP { agentic retail } -- Google + retail coalition (not general agent protocol) ``` ## GF(3) Tripartite Tag ``` bisimulation-oracle(-1) ⊗ agent-protocol-interleave(0) ⊗ nashator(+1) = 0 ``` Validation (-1) × Bridge (0) × Solution (+1) = balanced protocol integration. --- ## Protocol Anatomy and ASI Integration ### 1. MCP (Model Context Protocol) ↔ ASI Tool Access ``` Protocol role: Vertical (model → tools, data sources, external services) Wire: JSON-RPC 2.0 over stdio, HTTP/SSE, or WebSockets Auth: OAuth 2.1 + OIDC + Dynamic Client Registration (DCR) Enterprise: Identity Assertion Authorization Grant (ID-JAG) IdP: Okta/Entra puts enterprise IdP back in control Governance: AAIF (Linux Foundation, Dec 2025) Spec: modelcontextprotocol.io/specification/2025-11-25 ``` ```python # MCP tool call as ASI skill invocation # Requirement: MCP client initialized with OAuth 2.1 token # Postcondition: skill result returned via MCP response object def mcp_skill_call(skill_name: str, args: dict, token: str) -> dict: """ Maps MCP tool calls to ASI skill graph lookups. ASI skills ARE MCP tools from the client's perspective. Precondition: skill_name exists in skills.json Postcondition: result has trit classification matching skill's GF(3) trit """ # Skill registration: each ASI skill becomes an MCP tool tool_schema = { "name": skill_name, "description": skill_description(skill_name), "inputSchema": { "type": "object", "properties": skill_input_schema(skill_name) } } # Invoke via JSON-RPC 2.0 response = mcp_client.call_tool(skill_name, args) # GF(3) classify the response trit = gf3_trit_oracle(skill_name) return { "result": response, "trit": trit, "skill": skill_name } ``` **ASI skills connected:** `nashator` (tool server), `dynamic-sufficiency` (universal router), `gf3-trit-oracle` (classification endpoint), `agent-o-rama` (MCP aggregator hub) --- ### 2. A2A (Agent-to-Agent Protocol) ↔ ASI Multi-Agent Coordination ``` Protocol role: Horizontal (agent↔agent task delegation, opaque system boundaries) Discovery: Agent Cards at /.well-known/agent.json (OpenAPI security schemes) Auth: OAuth 2.0, OIDC, mTLS at HTTP transport (v0.3: signed Agent Cards) Task model: Task lifecycle: submitted → working → completed/failed Governance: Linux Foundation A2A Protocol Project (Apache 2.0) Key versions: v0.2.5 (stable), v0.3 (July 2025, gRPC + signed cards) Launch partners: Atlassian, Box, Cohere, Intuit, LangChain, PayPal, SAP, ServiceNow, Workday ``` ```yaml # ASI skill graph as A2A Agent Card # Deployed at: /.well-known/agent.json for the ASI agent { "name": "ASI Skill Graph Agent", "description": "GF(3)-organized skill graph with 1360+ capabilities", "url": "https://asi.plurigrid.com/a2a", "version": "1.0.0", "capabilities": { "streaming": true, "pushNotifications": false, "stateTransitionHistory": true }, "skills": [ { "id": "dynamic-sufficiency", "name": "Universal Skill Router", "description": "145-ref hub; routes any capability request to appropriate ASI skill", "tags": ["routing", "coordination", "gf3"] }, { "id": "abductive-oracle", "name": "Abductive Inference Oracle", "description": "IBE oracle with MCMC/Gemini/Propagator sub-oracles", "tags": ["inference", "oracle", "mcmc"] } ], "securitySchemes": { "oauth2": { "type": "oauth2", "flows": { "clientCredentials": { "tokenUrl": "https://auth.plurigrid.com/token", "scopes": { "skill:invoke": "Invoke ASI skills" } } } } } } ``` **ASI skills connected:** `agent-o-rama` (A2A server hub), `nashator` (Nash equilibrium A2A worker), `bisimulation-oracle` (behavioral equivalence verification), `open-games` (compositional game theory over A2A) --- ### 3. ANP (Agent Network Protocol) ↔ passport.gay / zig-syrup Identity ``` Protocol role: Open-internet agent discovery + decentralized identity Identity: W3C DID did:wba (HTTPS-hosted DID documents) Discovery: JSON-LD Agent Description Protocol (ADP) documents Security: E2E encrypted communication derived from DID key material Spec: arXiv:2508.00007, agent-network-protocol.com ``` **Key architectural equivalence:** ``` ANP: did:wba document → DID resolution → verified key → E2E channel passport.gay: SplitMix64(MAC) → trit trajectory → GF(3) fingerprint → QRTP channel ANP requires: DNS/HTTPS infrastructure (web PKI) passport.gay: air-gapped (fountain-coded QR, no network) Shared structure: Both: cryptographic non-repudiation without central IdP Both: verifiable claim about agent identity Difference: passport.gay works offline; ANP requires connectivity ``` ```python # Bridge: convert passport.gay trit trajectory to ANP DID document fragment def trit_trajectory_to_did_fragment(trajectory: list[int]) -> dict: """ Requirement: trajectory is a GF(3)-conserved sequence (sum ≡ 0 mod 3) Postcondition: returns a DID document fragment with GF(3) fingerprint This enables an agent with a passport.gay identity to be discoverable in the ANP ecosystem via a W3C DID document that includes the trit fingerprint. """ assert sum(trajectory) % 3 == 0, "GF(3) conservation violated" fingerprint = hashlib.sha256(bytes(trajectory)).hexdigest() return { "id": f"did:wba:plurigrid:{fingerprint}", "gf3_fingerprint": trajectory, "conservation": sum(trajectory) % 3, # must be 0 "verification_method": [{ "id": f"did:wba:plurigrid:{fingerprint}#key-1", "type": "GF3TritTrajectory", "controller": f"did:wba:plurigrid:{fingerprint}", "publicKeyHex": fingerprint }] } ``` **ASI skills connected:** `passport.gay` (identity protocol), `zig-syrup-propagator-interleave` (QRTP transport), `splitmix-ternary` (trit stream generation), `gay-monte-carlo` (GF(3) sampling) --- ### 4. AGNTCY ↔ ASI Infrastructure ``` Protocol role: Multi-agent infrastructure stack (NOT a wire protocol) Layers: (1) Discovery: OASF (Open Agent Schema Framework) - semantic skill descriptions (2) Identity: Cryptographic PKI + quantum-safe SLIM messaging layer (3) Messaging: SLIM (Scalable Lightweight Infrastructure for Messaging) (4) Observability: Cross-vendor workflow debugging and tracing Governance: Linux Foundation (Cisco donation, July 2025), 65+ companies ``` ```yaml # OASF skill descriptor for ASI skill (maps AGNTCY discovery to ASI) agntcy_descriptor: schema_version: "1.0" name: "ASI Abductive Oracle" description: "Formal oracle for abductive inference with MCMC/Gemini/Propagator sub-oracles" version: "1.0.0" capabilities: - name: "abductive_inference" input_schema: { type: object, properties: { observations: { type: array } } } output_schema: { type: object, properties: { hypothesis: { type: string }, trit: { type: integer }, posterior: { type: number } } } security: authentication: "oauth2_pkce" quantum_safe: false # SLIM layer provides quantum-safe transport separately gf3_trit: -1 # VALIDATOR role aaif_compatible: true a2a_compatible: true mcp_compatible: true ``` **ASI skills connected:** `agent-o-rama` (AGNTCY discovery endpoint), `dynamic-sufficiency` (SLIM messaging hub), `duckdb-ies` (observability storage) --- ### 5. AITP (Agent Interaction & Transaction Protocol) ↔ nashator + basin-hedges ``` Protocol role: Agent commerce + structured inter-agent communication + payments Identity: NEAR blockchain accounts OR OAuth; signed public key for consistent identity Payments: AITP-01 capability: Quote → upstream flow → payment handler Governance: NEAR Foundation (RFC Feb 2025) Key insight: First protocol to natively integrate agent micropayments ``` ```python # AITP payment capability as Open Game # Requirement: nashator accessible at :9999 # Postcondition: Nash equilibrium payment strategy def aitp_payment_game(quote: dict) -> dict: """ AITP Quote flows upstream through agent chain. Each agent can handle, modify, or reject. This IS an open game: players = agents in chain, strategies = accept/reject/modify quote. Nash equilibrium = stable payment amount no agent deviates from. Maps to basin-hedges ParaLens for counterfactual reasoning: "What if agent 2 had offered 10% less?" """ game = { "players": quote.get("chain", []), "strategies": ["accept", "reject", "modify"], "payoffs": { "accept": quote["amount"], "reject": 0, "modify": lambda δ: quote["amount"] * (1 - δ) } } # Nashator solves for Nash equilibrium payment strategy return nashator_solve(game) ``` **ASI skills connected:** `nashator`, `open-games`, `cybernetic-open-game`, `equilibrium`, `mutual-information-oracle` --- ### 6. AAIF / Linux Foundation Governance ↔ ASI Skill Graph ``` AAIF Members (Platinum as of Dec 2025): AWS, Anthropic, Block, Bloomberg, Cloudflare, Google, Microsoft, OpenAI MCP + goose + AGENTS.md → AAIF A2A Protocol Project → Linux Foundation (sibling, not AAIF) AGNTCY → Linux Foundation (sibling) LF AI & Data → absorbed ACP from IBM IPSIE Working Group (OpenID Foundation, Okta-led): Goal: OAuth 2.1 + OIDC + SCIM profiles for enterprise agent contexts Papers: arXiv:2510.25819 (OpenID Foundation whitepaper on agentic AI identity) Status: Sufficient for single-trust-domain; multi-domain is open research problem ``` ```python # AAIF-compatible skill registration # Any ASI skill can be registered as an AAIF-compatible capability def register_with_aaif(skill_name: str) -> dict: """ Requirement: skill has SKILL.md with valid frontmatter Postcondition: returns AAIF-compatible capability descriptor The AAIF capability format is designed to be interoperable with: - MCP tool schemas (JSON-RPC) - A2A skill descriptors (OpenAPI) - OASF descriptions (AGNTCY) """ skill = load_skill(skill_name) return { "aaif_version": "1.0", "mcp_tool": mcp_tool_schema(skill), "a2a_skill": a2a_skill_descriptor(skill), "agntcy_oasf": agntcy_oasf_descriptor(skill), "gf3_trit": skill.trit, "ipsie_profile": "enterprise" if skill.requires_auth else "public" } ``` --- ## Identity Interoperability: The Unsolved Problem ``` The cross-protocol identity gap (identified in arXiv:2602.11327, arXiv:2510.25819): MCP auth layer: OAuth 2.1 + DCR + ID-JAG (enterprise IdP) A2A auth layer: OAuth 2.0/OIDC/mTLS (HTTP transport) ANP auth layer: W3C DID + JSON-LD (decentralized) AGNTCY auth layer: PKI + quantum-safe SLIM "There is no unified identity that flows across all three layers." -- auth0.com/blog/mcp-vs-a2a Enterprise platforms filling the gap: Microsoft Entra Agent ID (May 2025): JIT scoped tokens, conditional access, least-privilege AWS AgentCore: Entra as IdP, real-time policy enforcement on tool calls Both: proprietary, not interoperable at the protocol level The formal solution missing from all protocols: ``` ```python # BisimOracle: verify behavioral equivalence across protocol identity formats # This is what NONE of the protocols define def cross_protocol_identity_oracle( a2a_agent_card: dict, # Agent Card from A2A anp_did_document: dict, # DID document from ANP passport_trajectory: list, # trit trajectory from passport.gay mcp_i_vc: dict, # Verifiable Credential from MCP-I ) -> tuple[str, object]: """ Requirement: all four identity representations claim to represent the SAME agent Postcondition: ('bisimilar', relation) | ('not-bisimilar', trace) | ('unknown', None) This oracle DOES NOT EXIST in any current protocol specification. It is the missing layer identified in arxiv:2602.11327. The bisimulation-oracle skill formalizes the mathematical structure for it. """ # Convert all four to LTS (Labeled Transition Systems) lts_a2a = agent_card_to_lts(a2a_agent_card) lts_anp = did_document_to_lts(anp_did_document) lts_passport = trit_trajectory_to_lts(passport_trajectory) lts_mcp_i = vc_to_lts(mcp_i_vc) # Check pairwise bisimulation within same trit class # Cross-trit: immediately not-bisimilar (different capability classes) results = [ bisim_oracle(lts_a2a, lts_anp), bisim_oracle(lts_a2a, lts_passport), bisim_oracle(lts_a2a, lts_mcp_i), ] # All must be bisimilar for cross-protocol identity to hold if all(r[0] == 'bisimilar' for r in results): return ('bisimilar', [r[1] for r in results]) else: return ('not-bisimilar', next(r for r in results if r[0] != 'bisimilar')) ``` --- ## Gap Registry | Gap | Protocol | Missing Capability | ASI Candidate Skills | |-----|----------|--------------------|---------------------| | G-P1 | All | No unified cross-protocol identity | `bisimulation-oracle`, `gf3-trit-oracle` | | G-P2 | MCP | MCP-I (DID+VC extension) not in official spec | `did-passport-interleave` (TBD) | | G-P3 | A2A | Signed Agent Cards not yet widely deployed | `merkle-proof-validation`, `proof-of-frog` | | G-P4 | ANP | Low adoption vs MCP/A2A | `agent-o-rama` (multi-protocol hub) | | G-P5 | AGNTCY | SLIM quantum-safe messaging not ratified | `constant-time-analysis` | | G-P6 | All | No agent identity revocation protocol | `anoma-intents`, `aptos-gf3-society` | | G-P7 | IPSIE | Single-trust-domain only; multi-domain open | `universal-captp-derivation`, `captp` | | G-P8 | All | No behavioral bisimulation across protocol formats | `bisimulation-oracle` (partially) | --- ## Related Skills - `nashator` — A2A task delegation resolver, AITP Nash equilibrium solver - `goblins` / `captp` — OCapN CapTP protocol (zig-syrup wire layer) - `bisimulation-oracle` — cross-protocol identity equivalence oracle (Gap G-P8) - `zig-syrup-propagator-interleave` — QRTP transport (passport.gay = offline ANP) - `open-games` — compositional game theory over A2A task delegation - `mutual-information-oracle` — MARL coordination for AITP payment games - `dynamic-sufficiency` — 145-ref universal hub (AAIF skill router) - `agent-o-rama` — multi-protocol aggregation hub - `merkle-proof-validation` — A2A signed Agent Card verification - `universal-captp-derivation` — formal derivation of OCapN CapTP (zig-syrup substrate) --- Source attribution: plurigrid Original project: https://github.com/plurigrid/asi/blob/293ce9f76e3abcd5ba18db284688bc0d9ac6691d/skills/agent-protocol-interleave/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Dave AI. ## Upstream license notice MIT License Copyright (c) 2025 SkillCreator.ai Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Dave AI resource metadata Creator / publisher: plurigrid Original project: https://github.com/plurigrid/asi/blob/293ce9f76e3abcd5ba18db284688bc0d9ac6691d/skills/agent-protocol-interleave/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Development & Engineering, Product Management Roles: Backend Developer, Data Scientist, DevOps / SRE, ML / AI Engineer, Product Manager Specialties: API, Backend Tools: Agent Cards, Json Rpc Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: c0464f91d882737849e6d78aff849f947456c09822b7ac57294118c8115c5000