{
  "context": "This evaluation assesses the engineer's proficiency in using PyMISP's advanced analysis features, specifically analyst data capabilities (notes and opinions), event report creation, and decay model integration for indicator lifecycle management.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Add analyst note",
      "description": "Uses PyMISP's add_analyst_data() or similar method to attach a note to an event. The implementation should correctly specify the object_type as 'Event' and data_type as 'note', passing the note content appropriately.",
      "max_score": 20
    },
    {
      "name": "Add analyst opinion",
      "description": "Uses PyMISP's add_analyst_data() or similar method to attach an opinion with a numeric rating (0-100) to an event. The implementation should correctly specify the object_type as 'Event' and data_type as 'opinion', passing the opinion value appropriately.",
      "max_score": 20
    },
    {
      "name": "Create event report",
      "description": "Uses PyMISP's add_event_report() method to attach a narrative report to an event. Should create a MISPEventReport object or pass report content directly with the event ID.",
      "max_score": 20
    },
    {
      "name": "Include decay scores",
      "description": "Configures search parameters to include decay scores in results, using the includeDecayScore parameter or similar in search() or search_index() methods.",
      "max_score": 15
    },
    {
      "name": "Filter decayed attributes",
      "description": "Applies filtering to exclude decayed attributes from search results, using parameters like decayingModel, excludeDecayed, or score filtering in the search query.",
      "max_score": 15
    },
    {
      "name": "Handle API responses",
      "description": "Properly handles return values from API calls, checking for success/failure and extracting relevant data from response objects.",
      "max_score": 10
    }
  ]
}