{
  "context": "Evaluates how well the solution uses azure-ai-documentintelligence batch analysis APIs to launch blob-based runs, resume them from continuation tokens, enumerate operations, and clean up stored batch results.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Batch request",
      "description": "Uses DocumentIntelligenceClient.begin_analyze_batch_documents with the provided model_id and an AnalyzeBatchDocumentsRequest that sets azure_blob_source or azure_blob_file_list_source along with result_container_url, optional result_prefix, and overwrite_existing when requested.",
      "max_score": 30
    },
    {
      "name": "Capture tokens",
      "description": "Extracts the operation_id from the begin_analyze_batch_documents poller details and obtains a continuation_token from that poller for later resumption.",
      "max_score": 15
    },
    {
      "name": "Resume status",
      "description": "Resumes a batch run via get_analyze_batch_result using the continuation_token and reads the AnalyzeBatchResult from the returned poller to surface status plus succeeded_count, failed_count, and skipped_count.",
      "max_score": 20
    },
    {
      "name": "List operations",
      "description": "Calls list_analyze_batch_results with skip/top parameters and maps each AnalyzeBatchOperation to summaries containing operation_id, status, and percent_completed when present.",
      "max_score": 20
    },
    {
      "name": "Delete result",
      "description": "Invokes delete_analyze_batch_result with the given model_id and result_id to remove stored batch analysis outputs as part of the cleanup flow.",
      "max_score": 15
    }
  ]
}