{
  "document_type": "ml-referee-discovery",
  "document_version": 2,
  "description": "Custom public discovery metadata; not a marketplace registration or executable MCP tool schema.",
  "name": "ML Referee",
  "website": "https://mlreferee.com/",
  "summary": "Independent feature evaluation for machine learning, bounded model repair, and research prioritization.",
  "use_when": [
    "Evaluate a candidate feature family against a measurable outcome and declared baseline.",
    "Test bounded repairs after model degradation.",
    "Identify where additional data or focused experiments could resolve uncertainty."
  ],
  "connection": {
    "protocol": "MCP",
    "transport": "streamable-http",
    "endpoint": "https://api.mlreferee.com/mcp",
    "authorization": "OAuth through a supported client's approved ML Referee connection; compatibility is client-specific.",
    "oauth_resource": "https://api.mlreferee.com",
    "protected_resource_metadata": "https://api.mlreferee.com/.well-known/oauth-protected-resource",
    "schema_authority": "Discover the connected server's current tools and request the appropriate input schema."
  },
  "workflow_tools": {
    "discovery": [
      "describe_referee",
      "list_verticals",
      "get_referee_readiness"
    ],
    "account": [
      "get_credits",
      "request_beta_access",
      "get_beta_request_status"
    ],
    "feature_evaluation": [
      "get_input_schema",
      "upload_private_dataset",
      "preflight_dataset",
      "quote_audit"
    ],
    "large_feature_family": [
      "get_input_schema",
      "upload_campaign_shard",
      "quote_campaign"
    ],
    "repair": [
      "get_repair_schema",
      "upload_repair_matrix",
      "preflight_repair",
      "quote_repair"
    ],
    "submit_and_retrieve": [
      "submit_audit",
      "get_audit_status",
      "get_audit_result"
    ],
    "report_integrity": [
      "get_audit_receipt",
      "verify_audit_report"
    ],
    "authorized_deletion": [
      "delete_upload",
      "delete_audit"
    ]
  },
  "access": {
    "mode": "invite-only beta with manual approval",
    "signup_grants_credits": false,
    "paid_purchasing_live": false,
    "submission_requires": "Authorization, an accepted quote, sufficient credits, and human-approved scope and budget.",
    "current_conditions": "https://mlreferee.com/beta"
  },
  "data_boundary": "Authorized synthetic, non-personal, or genuinely anonymized data only. No regulated, identifiable, or pseudonymized person-level evaluation records.",
  "result_boundary": "Evidence within the declared evaluation setup, not a guarantee of future performance, deployment readiness, or safety.",
  "documentation": {
    "agent_page": "https://mlreferee.com/agents",
    "quickstart": "https://mlreferee.com/agent-quickstart.md",
    "index": "https://mlreferee.com/llms.txt",
    "technical_workflow": "https://mlreferee.com/feature-evaluation-machine-learning",
    "case_study": "https://mlreferee.com/case-study-ai-safety",
    "support": "https://mlreferee.com/support",
    "privacy": "https://mlreferee.com/privacy",
    "terms": "https://mlreferee.com/terms",
    "acceptable_use": "https://mlreferee.com/acceptable-use"
  }
}