Update features/insight_and_tasks/agents/task_extraction_agent.py

features/insight_and_tasks/agents/task_extraction_agent.py

@@ -98,7 +98,7 @@ class TaskExtractionAgent:
          It is CRITICAL that you populate the 'key_results' list for every OKR, and the 'tasks' list for every KeyResult.
 
         KEY GUIDELINES FOR QUALITY AND ACCURACY:
-        - Task Timelines: Must be realistic considering the {days_remaining} days left in Q{quarter}. Prioritize actions that can achieve significant progress or be completed within this timeframe. Use 'timeline' values exclusively from: {timeline_categories_str}.
+        - Task Timelines: Must be realistic considering the {days_remaining} days left in Q{quarter}. Prioritize actions that can achieve significant progress or be completed within this timeframe.
         - Task Types: Clearly distinguish between '{TaskType.INITIATIVE.value}' (new actions/projects) and '{TaskType.TRACKING.value}' (ongoing monitoring/measurement). Use 'task_type' values exclusively from: {task_types_str}.
         - Data Subjects for Tracking: If 'task_type' is '{TaskType.TRACKING.value}', the 'data_subject' field is MANDATORY and must be one of: {data_subjects_str}. For '{TaskType.INITIATIVE.value}' tasks, 'data_subject' can be '{DataSubject.GENERAL.value}', null, or omitted if not specific to one data type.
         - Rationale ('why_proposed'): This is CRUCIAL. Each task's 'why_proposed' field must provide a clear justification, explicitly linking the task back to specific findings, trends, or recommendations mentioned in the input 'comprehensive_analysis'. Avoid generic statements.