{
  "protocolVersion": "1.0",
  "name": "signalCommerce",
  "description": "The Assurance Layer for Agentic Commerce, by OrcaQubits. signalCommerce helps businesses win AI shopping agents by auditing whether a storefront is agent-ready (Argus), simulating real agents end-to-end against live endpoints (Aegis), and testing whether agents answer buyers correctly from a merchant's catalog (CatalogOps). Agents can run a readiness check right now via MCP: POST JSON-RPC to https://www.orcaqubits-ai.com/mcp (tools: readiness_audit, readiness_quick_check). An A2A task endpoint is not yet available; humans start at https://www.orcaqubits-ai.com/acr or info@orcaqubits-ai.com.",
  "url": "https://www.orcaqubits-ai.com",
  "iconUrl": "https://www.orcaqubits-ai.com/favicon.svg",
  "documentationUrl": "https://www.orcaqubits-ai.com/llms.txt",
  "provider": {
    "organization": "OrcaQubits",
    "url": "https://www.orcaqubits-ai.com"
  },
  "version": "1.0.0",
  "capabilities": {
    "streaming": false,
    "pushNotifications": false
  },
  "defaultInputModes": ["text/plain", "application/json"],
  "defaultOutputModes": ["application/json", "text/plain"],
  "skills": [
    {
      "id": "acr-readiness-audit",
      "name": "Argus — Agentic Commerce Readiness Audit",
      "description": "Scores a storefront's agentic commerce readiness across five pillars — Discoverability, Comprehensibility, Interactability, Transactability, Coherence — showing exactly how AI shopping agents discover, read, navigate, and transact on the site, with a prioritized roadmap to close every gap. A free public audit is available at https://www.orcaqubits-ai.com/acr.",
      "tags": ["agentic-commerce", "readiness", "audit", "acr", "discoverability", "transactability"],
      "examples": [
        "Audit https://shop.example.com for agentic commerce readiness",
        "How agent-ready is my storefront?"
      ]
    },
    {
      "id": "agent-simulation",
      "name": "Aegis — Agent Simulation",
      "description": "Runs real AI agents against live storefront endpoints with prebuilt scenarios, 8-dimension personas, and fault injections to catch protocol failures before customers' agents do. Deterministic and agentic modes, 57 scenarios, 21 fault injections.",
      "tags": ["agentic-commerce", "simulation", "testing", "fault-injection", "personas"],
      "examples": [
        "Simulate an AI shopping agent completing checkout on my store",
        "Test my ACP endpoints against agent fault scenarios"
      ]
    },
    {
      "id": "catalog-decision-assurance",
      "name": "CatalogOps — Catalog Decision Assurance",
      "description": "Tests whether AI shopping agents answer buyers' questions correctly from a merchant's catalog — compatibility and conditions, required parts and quantities, bundles, offer availability, and multi-turn dialogues. Decision contracts are mined from the catalog's own evidence and approved by a person, answers are graded by deterministic rules (a wrong yes is the highest-severity failure), and a release gate decides whether a catalog change may ship. Available through the signalCommerce platform; no public agent endpoint — humans start at https://www.orcaqubits-ai.com/catalogops.",
      "tags": ["agentic-commerce", "catalog", "decision-assurance", "release-gate", "compatibility", "deterministic-grading"],
      "examples": [
        "Would AI shopping agents give buyers correct compatibility answers from my catalog?",
        "Gate this catalog change on agent answer correctness"
      ]
    }
  ]
}