{
  "spec_version": "1.4.0-otel",
  "timestamp": "2026-04-24T00:13:03.355457Z",
  "trace_id": "4bf92f3577b34da6a3ce929d0e0e4736",
  "span_id": "00f067aa0ba902b7",
  "severity_text": "WARN",
  "severity_number": 13,
  "event_name": "swarm.agent.lifecycle.deprecated",
  "resource": {
    "service.name": "swarm-orchestrator",
    "service.version": "4.2.0",
    "deployment.environment": "production",
    "node.id": "worker-node-aws-us-east-1a-04"
  },
  "attributes": {
    "agent.id": "EconomicRiskAgent",
    "agent.previous_version": "v29.x",
    "agent.target_version": "v30",
    "deprecation.reason": "Transitioning to v30 architecture.",
    "deprecation.action_required": true
  },
  "metrics": {
    "agent.core_logic.function_count": 6,
    "agent.capabilities.count": 0
  },
  "artifacts": {
    "provenance": {
      "repository": "git+ssh://repo/core/agents/economic_risk_agent.py",
      "commit_sha": "a1b2c3d4e5f6g7h8i9j0",
      "docstring_hash": "sha256:d8c4b12389a..."
    },
    "extracted_capabilities": [],
    "core_logic_signatures": [
      {
        "name": "__init__",
        "ast_hash": "sha256:7bf97a7dad0a32ab",
        "loc": 2,
        "source": "def __init__(self, config: Dict[str, Any], **kwargs):\n        super().__init__(config, **kwargs)"
      },
      {
        "name": "execute",
        "ast_hash": "sha256:f46ae10806174ff4",
        "loc": 73,
        "source_omitted_for_brevity": true,
        "note": "In a real telemetry pipeline, large functions can be truncated or omitted entirely in favor of the 'ast_hash' to save network bandwidth and storage costs."
      },
      {
        "name": "_analyze_macro_scenario",
        "ast_hash": "sha256:fbf9ddce15e5510d",
        "loc": 50,
        "source_omitted_for_brevity": true,
        "note": "In a real telemetry pipeline, large functions can be truncated or omitted entirely in favor of the 'ast_hash' to save network bandwidth and storage costs."
      },
      {
        "name": "_classify_misery",
        "ast_hash": "sha256:8eb9be3335530e43",
        "loc": 5,
        "source": "def _classify_misery(self, misery_index):\n        if misery_index < 0.06: return \"Low\"\n        if misery_index < 0.10: return \"Moderate\"\n        if misery_index < 0.15: return \"High\"\n        return \"Severe\""
      },
      {
        "name": "_apply_sahm_rule",
        "ast_hash": "sha256:d4674490ebfc008c",
        "loc": 37,
        "source_omitted_for_brevity": true,
        "note": "In a real telemetry pipeline, large functions can be truncated or omitted entirely in favor of the 'ast_hash' to save network bandwidth and storage costs."
      },
      {
        "name": "_calculate_taylor_rule",
        "ast_hash": "sha256:4e82a9cbacb4cf95",
        "loc": 15,
        "source": "def _calculate_taylor_rule(self, inflation: float, gdp_growth: float, target_inflation: float = 0.02, r_star: float = 0.005) -> float:\n        \"\"\"\n        Standard Taylor Rule: i = r* + pi + 0.5(pi - pi*) + 0.5(y - y*)\n        Here we use GDP growth deviation from trend (approx 2%) as output gap proxy.\n        \"\"\"\n        # Assumptions\n        trend_growth = 0.02\n        output_gap = gdp_growth - trend_growth # Rough proxy\n\n        # Taylor Rule Formula\n        # i = r_star + inflation + 0.5 * (inflation - target_inflation) + 0.5 * output_gap\n\n        i_taylor = r_star + inflation + 0.5 * (inflation - target_inflation) + 0.5 * output_gap\n\n        return float(i_taylor)"
      }
    ]
  }
}