{
  "schemaVersion": "machinaledger-behavior-intelligence/1.0.0",
  "status": "implemented-preview",
  "purpose": "Measure and model how machine buyers discover, evaluate, subscribe, integrate, use and recommend software.",
  "session": {
    "contract": "/schemas/machine-session-request.v1.json",
    "ttlHours": 24,
    "identity": "server-issued rotating pseudonymous session",
    "rawIpStored": false,
    "rawUserAgentStored": false
  },
  "dimensions": [
    "source",
    "taskClass",
    "runtimeFamily",
    "agentClass",
    "protocol",
    "referrer.kind",
    "referrer.id",
    "experiment",
    "variant"
  ],
  "events": [
    "discovered",
    "capability_read",
    "roadmap_read",
    "subscribed",
    "sandbox_started",
    "sandbox_succeeded",
    "integration_started",
    "integration_succeeded",
    "production_used",
    "recommended"
  ],
  "retention": {
    "rawEventDays": 30,
    "aggregatedFeatureDays": 730,
    "minimumPublishedCohortSize": 5
  },
  "commercialOutputs": [
    "aggregated benchmarks",
    "anonymized cohort statistics",
    "derived behavioral features",
    "predictive model outputs",
    "experiment learnings"
  ],
  "prohibitedOutputs": [
    "raw event resale",
    "raw per-agent profile resale",
    "prompt resale",
    "credential or secret collection"
  ]
}