Krow-workspace/apps/mobile/NEXT_SPRINT_TASKS.md

Recommended tasks for the next sprint

• In the mobile applications, since the structure is now finalized (at least for the existing features), we need to strictly follow best practices while coding:
  • Break down large widgets into smaller, reusable widgets
  • Add doc comments where necessary to improve readability and maintainability
  • Remove overly complicated or unnecessary logic introduced by AI and simplify where possible
• Improvement points

• apps/mobile/packages/features/client/client_coverage/lib/src/data/repositories_impl/coverage_repository_impl.dart

  • Fix the location field in CoverageShiftRole to use the correct fallback logic.
  • line 125 remove redundant location values.

• Update the dataconnect docs.

• Track lat and lng in the staff preferred work locations (for now we are only storing the name).

• Change the name of the dataconnect connector replacing the "ExampleConnecter" with "KrowConnecter"

• final String status; in OrderItem make it an enum.

• /// Date of the shift (ISO format). final String date; make this in the DateTime format instead of string.

• in view_orders_cubit.dart combine the logic of _calculateUpNextCount and _calculateTodayCount into a single function that calculates both counts together to avoid redundant filtering of orders.

• In places api call in the when the api's not working we need to show a proper error message instead of just an empty list.

• pending should come first in the view order list.

• track minimum shift hours in the staff profile and show a warning if they try to apply for shifts that are below their minimum hours.

  • this need to be added in the BE and also a FE validation (5 hrs).

• Cannot cancel before 24 hours of the shift start time. If do we should charge for 4 hours of work for each shifts.

• verify the order creation process in the client app.

  • Vendor don't need to verify the order, when the order is created it should be automatically published.
  • rethink the order status, we need to simplify it.

• Validation layer

  • Profile info
  • emergency contact
  • experiences
  • attires
    • there should be manual verification by the client even if the ai verification is passed.
    • to track false positives and false negatives.
  • certifications
    • there should be manual verification by the client even if the ai verification is passed.
    • to track false positives and false negatives.
  • documents
  • tax forms