{
  "context": "This criteria evaluates how well the engineer uses Kedro's dataset lifecycle hook system to implement a monitoring solution that tracks dataset load and save operations during pipeline execution.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Hook class implementation",
      "description": "Implements a class that properly uses Kedro's hook specifications (e.g., using @hook_impl decorator or implementing hook spec methods from kedro.framework.hooks)",
      "max_score": 25
    },
    {
      "name": "after_dataset_loaded hook",
      "description": "Correctly implements the after_dataset_loaded hook method to capture dataset load operations with the proper signature including dataset_name parameter",
      "max_score": 25
    },
    {
      "name": "after_dataset_saved hook",
      "description": "Correctly implements the after_dataset_saved hook method to capture dataset save operations with the proper signature including dataset_name parameter",
      "max_score": 25
    },
    {
      "name": "Timestamp generation",
      "description": "Generates ISO 8601 formatted timestamps for each logged operation using appropriate datetime methods",
      "max_score": 10
    },
    {
      "name": "Log storage",
      "description": "Stores log entries in a data structure that preserves chronological order and can be retrieved via get_log method",
      "max_score": 10
    },
    {
      "name": "Log data structure",
      "description": "Creates log entries with the exact structure specified (dataset_name, operation, timestamp fields) as dictionaries",
      "max_score": 5
    }
  ]
}