{
  "context": "Evaluates whether the solution uses azure-ai-documentintelligence long-running analysis features to control polling cadence, surface operation metadata, and resume work with continuation tokens. Focuses on proper poller usage for starting, resuming, and finalizing document analysis jobs.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Custom polling",
      "description": "Starts document analysis with an explicit `polling_interval` override (via `begin_analyze_document(..., polling_interval=...)` or client initialization) matching the requested cadence.",
      "max_score": 25
    },
    {
      "name": "Poller metadata",
      "description": "Retrieves the operation identifier from `AnalyzeDocumentLROPoller.details` (e.g., `details['operation_id']`) and returns it as part of the job output.",
      "max_score": 25
    },
    {
      "name": "Continuation capture",
      "description": "Captures a continuation token from the poller using the SDK method (e.g., `poller.continuation_token()`), not a fabricated placeholder, and exposes it for later resume.",
      "max_score": 20
    },
    {
      "name": "Resume from token",
      "description": "Resumes a previous analysis using the SDK's continuation support (`AnalyzeDocumentLROPoller.from_continuation_token(...)` or `begin_analyze_document(..., continuation_token=token)`) without re-uploading the document.",
      "max_score": 20
    },
    {
      "name": "Result retrieval",
      "description": "Obtains completed analysis content through the poller (`poller.result()` or async equivalent) after start/resume rather than bypassing the LRO machinery.",
      "max_score": 10
    }
  ]
}