{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "$id": "agent_confidence_tracking.schema.json",
  "title": "Agent Confidence Tracking Schema",
  "description": "Schema for multi-dimensional confidence tracking with statistical aggregations and uncertainty quantification",
  "type": "object",
  "required": [
    "agentId",
    "timestamp",
    "context",
    "confidence",
    "prediction",
    "temporal",
    "learning",
    "metadata"
  ],
  "properties": {
    "_id": {
      "type": "string",
      "description": "MongoDB ObjectId"
    },
    "agentId": {
      "type": "string",
      "description": "Unique identifier for the agent",
      "minLength": 1,
      "maxLength": 100
    },
    "sessionId": {
      "type": "string",
      "description": "Session identifier for confidence tracking",
      "minLength": 1,
      "maxLength": 100
    },
    "timestamp": {
      "type": "string",
      "format": "date-time",
      "description": "When this confidence measurement was recorded"
    },
    "context": {
      "type": "object",
      "description": "Context of the confidence measurement",
      "required": ["task", "taskType", "domain", "complexity", "novelty", "stakes"],
      "properties": {
        "task": {
          "type": "string",
          "description": "What task/decision this confidence relates to",
          "maxLength": 500
        },
        "taskType": {
          "type": "string",
          "description": "Type of task",
          "enum": ["prediction", "classification", "generation", "reasoning", "decision"]
        },
        "domain": {
          "type": "string",
          "description": "Domain of expertise",
          "maxLength": 100
        },
        "complexity": {
          "type": "number",
          "description": "Task complexity (0-1 scale)",
          "minimum": 0,
          "maximum": 1
        },
        "novelty": {
          "type": "number",
          "description": "How novel/unfamiliar the task is (0-1 scale)",
          "minimum": 0,
          "maximum": 1
        },
        "stakes": {
          "type": "string",
          "description": "Importance of being correct",
          "enum": ["low", "medium", "high", "critical"]
        }
      },
      "additionalProperties": false
    },
    "confidence": {
      "type": "object",
      "description": "Multi-dimensional confidence measurements",
      "required": ["overall", "epistemic", "aleatoric", "calibrated", "aspects", "sources"],
      "properties": {
        "overall": {
          "type": "number",
          "description": "Overall confidence score (0-1)",
          "minimum": 0,
          "maximum": 1
        },
        "epistemic": {
          "type": "number",
          "description": "Knowledge-based uncertainty (0-1)",
          "minimum": 0,
          "maximum": 1
        },
        "aleatoric": {
          "type": "number",
          "description": "Data-based uncertainty (0-1)",
          "minimum": 0,
          "maximum": 1
        },
        "calibrated": {
          "type": "number",
          "description": "Calibrated confidence (0-1)",
          "minimum": 0,
          "maximum": 1
        },
        "aspects": {
          "type": "object",
          "description": "Confidence breakdown by aspect",
          "required": ["factualAccuracy", "completeness", "relevance", "clarity", "appropriateness"],
          "properties": {
            "factualAccuracy": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            },
            "completeness": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            },
            "relevance": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            },
            "clarity": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            },
            "appropriateness": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            }
          },
          "additionalProperties": false
        },
        "sources": {
          "type": "object",
          "description": "Confidence sources",
          "required": ["modelIntrinsic", "retrievalQuality", "contextRelevance", "historicalPerformance", "domainExpertise"],
          "properties": {
            "modelIntrinsic": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            },
            "retrievalQuality": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            },
            "contextRelevance": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            },
            "historicalPerformance": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            },
            "domainExpertise": {
              "type": "number",
              "minimum": 0,
              "maximum": 1
            }
          },
          "additionalProperties": false
        }
      },
      "additionalProperties": false
    },
    "prediction": {
      "type": "object",
      "description": "Prediction/decision details",
      "required": ["type", "value"],
      "properties": {
        "type": {
          "type": "string",
          "description": "Type of prediction",
          "enum": ["binary", "multiclass", "regression", "ranking", "generation"]
        },
        "value": {
          "description": "The actual prediction/decision made"
        },
        "alternatives": {
          "type": "array",
          "description": "Alternative predictions",
          "items": {
            "type": "object",
            "required": ["value", "confidence", "reasoning"],
            "properties": {
              "value": {
                "description": "Alternative prediction value"
              },
              "confidence": {
                "type": "number",
                "minimum": 0,
                "maximum": 1
              },
              "reasoning": {
                "type": "string",
                "maxLength": 500
              }
            }
          },
          "maxItems": 10
        },
        "probability": {
          "type": "number",
          "description": "Predicted probability",
          "minimum": 0,
          "maximum": 1
        },
        "distribution": {
          "type": "array",
          "description": "Full probability distribution",
          "items": {
            "type": "object",
            "required": ["value", "probability"],
            "properties": {
              "value": {
                "description": "Distribution value"
              },
              "probability": {
                "type": "number",
                "minimum": 0,
                "maximum": 1
              }
            }
          },
          "maxItems": 20
        }
      },
      "additionalProperties": false
    },
    "actual": {
      "type": "object",
      "description": "Actual outcome for calibration",
      "required": ["value", "correct", "verificationTime", "verificationSource"],
      "properties": {
        "value": {
          "description": "The actual correct answer/outcome"
        },
        "correct": {
          "type": "boolean",
          "description": "Whether the prediction was correct"
        },
        "accuracy": {
          "type": "number",
          "description": "Accuracy score (0-1) for continuous predictions",
          "minimum": 0,
          "maximum": 1
        },
        "feedback": {
          "type": "string",
          "description": "Human feedback on the prediction",
          "maxLength": 1000
        },
        "verificationTime": {
          "type": "string",
          "format": "date-time",
          "description": "When the outcome was verified"
        },
        "verificationSource": {
          "type": "string",
          "description": "Source of verification",
          "enum": ["automatic", "human", "external_system"]
        }
      },
      "additionalProperties": false
    },
    "calibration": {
      "type": "object",
      "description": "Computed calibration metrics",
      "required": ["brier", "logLoss", "reliability", "resolution", "sharpness", "overconfidence", "underconfidence"],
      "properties": {
        "brier": {
          "type": "number",
          "description": "Brier score",
          "minimum": 0,
          "maximum": 1
        },
        "logLoss": {
          "type": "number",
          "description": "Log loss",
          "minimum": 0
        },
        "reliability": {
          "type": "number",
          "description": "Reliability (calibration) score",
          "minimum": 0,
          "maximum": 1
        },
        "resolution": {
          "type": "number",
          "description": "Resolution (discrimination) score",
          "minimum": 0,
          "maximum": 1
        },
        "sharpness": {
          "type": "number",
          "description": "Sharpness (confidence) score",
          "minimum": 0,
          "maximum": 1
        },
        "overconfidence": {
          "type": "number",
          "description": "Measure of overconfidence bias",
          "minimum": 0,
          "maximum": 1
        },
        "underconfidence": {
          "type": "number",
          "description": "Measure of underconfidence bias",
          "minimum": 0,
          "maximum": 1
        }
      },
      "additionalProperties": false
    },
    "temporal": {
      "type": "object",
      "description": "Temporal aspects of confidence",
      "required": ["decayRate", "halfLife"],
      "properties": {
        "decayRate": {
          "type": "number",
          "description": "How quickly confidence should decay (per hour)",
          "minimum": 0,
          "maximum": 1
        },
        "halfLife": {
          "type": "number",
          "description": "Half-life of confidence relevance (hours)",
          "minimum": 0.1,
          "maximum": 8760
        },
        "expiresAt": {
          "type": "string",
          "format": "date-time",
          "description": "When this confidence measurement expires"
        },
        "seasonality": {
          "type": "string",
          "description": "Time-based patterns",
          "maxLength": 50
        }
      },
      "additionalProperties": false
    },
    "learning": {
      "type": "object",
      "description": "Learning and adaptation metrics",
      "required": ["surprisal", "informationGain", "modelUpdate", "confidenceAdjustment"],
      "properties": {
        "surprisal": {
          "type": "number",
          "description": "How surprising was the actual outcome",
          "minimum": 0
        },
        "informationGain": {
          "type": "number",
          "description": "How much we learned from this instance",
          "minimum": 0,
          "maximum": 1
        },
        "modelUpdate": {
          "type": "boolean",
          "description": "Whether this should trigger model updates"
        },
        "confidenceAdjustment": {
          "type": "number",
          "description": "Suggested adjustment to future confidence",
          "minimum": -1,
          "maximum": 1
        }
      },
      "additionalProperties": false
    },
    "metadata": {
      "type": "object",
      "description": "Confidence measurement metadata",
      "required": ["framework", "model", "version", "features", "computationTime"],
      "properties": {
        "framework": {
          "type": "string",
          "description": "AI framework used",
          "enum": ["mastra", "vercel-ai", "langchain", "openai-agents", "custom"]
        },
        "model": {
          "type": "string",
          "description": "AI model used",
          "maxLength": 100
        },
        "version": {
          "type": "string",
          "description": "Schema version",
          "pattern": "^\\d+\\.\\d+\\.\\d+$"
        },
        "features": {
          "type": "array",
          "description": "Features used for this prediction",
          "items": {
            "type": "string",
            "maxLength": 100
          },
          "maxItems": 20
        },
        "computationTime": {
          "type": "number",
          "description": "Time taken to compute (ms)",
          "minimum": 0
        },
        "memoryUsage": {
          "type": "number",
          "description": "Memory used (MB)",
          "minimum": 0
        }
      },
      "additionalProperties": false
    },
    "createdAt": {
      "type": "string",
      "format": "date-time",
      "description": "When this document was created"
    },
    "updatedAt": {
      "type": "string",
      "format": "date-time",
      "description": "When this document was last updated"
    }
  },
  "additionalProperties": false,
  "examples": [
    {
      "agentId": "customer-support-agent-001",
      "sessionId": "session_confidence_123",
      "timestamp": "2024-01-15T10:30:00Z",
      "context": {
        "task": "Classify customer sentiment from support ticket",
        "taskType": "classification",
        "domain": "customer_service",
        "complexity": 0.6,
        "novelty": 0.3,
        "stakes": "high"
      },
      "confidence": {
        "overall": 0.85,
        "epistemic": 0.15,
        "aleatoric": 0.10,
        "calibrated": 0.82,
        "aspects": {
          "factualAccuracy": 0.90,
          "completeness": 0.85,
          "relevance": 0.95,
          "clarity": 0.80,
          "appropriateness": 0.88
        },
        "sources": {
          "modelIntrinsic": 0.85,
          "retrievalQuality": 0.75,
          "contextRelevance": 0.90,
          "historicalPerformance": 0.82,
          "domainExpertise": 0.78
        }
      },
      "prediction": {
        "type": "multiclass",
        "value": "frustrated",
        "alternatives": [
          {
            "value": "angry",
            "confidence": 0.65,
            "reasoning": "Strong negative language but not extreme"
          },
          {
            "value": "disappointed",
            "confidence": 0.45,
            "reasoning": "Some disappointment indicators present"
          }
        ],
        "probability": 0.85,
        "distribution": [
          { "value": "frustrated", "probability": 0.85 },
          { "value": "angry", "probability": 0.10 },
          { "value": "disappointed", "probability": 0.05 }
        ]
      },
      "temporal": {
        "decayRate": 0.1,
        "halfLife": 24,
        "expiresAt": "2024-01-16T10:30:00Z",
        "seasonality": "business_hours"
      },
      "learning": {
        "surprisal": 0.2,
        "informationGain": 0.15,
        "modelUpdate": false,
        "confidenceAdjustment": 0.02
      },
      "metadata": {
        "framework": "mastra",
        "model": "gpt-4",
        "version": "1.0.0",
        "features": ["text_analysis", "sentiment_keywords", "context_history"],
        "computationTime": 150,
        "memoryUsage": 25
      }
    }
  ]
}