
Over three months, Magicode contributed to the Planning-Inspectorate/appeals-back-office repository by building and enhancing features that streamline hearing management and improve data integrity for planning appeals. They developed new API layers and database schemas using TypeScript and JavaScript to support hearing estimates, address capture, and validation workflows, integrating these with both frontend and backend components. Their work included refining user interfaces with HTML and CSS, implementing robust error handling, and ensuring accurate document management. By focusing on end-to-end feature delivery and consistent validation, Magicode improved communication flows, reduced manual intervention, and enhanced the reliability and usability of the appeals processing system.

May 2025 performance summary for Planning-Inspectorate/appeals-back-office. Delivered two major end-to-end features around hearing management and consistently improved reliability through UI/UX tweaks and robust error handling. Implemented a new data model and API layer to support hearing estimates, and established a structured hearing details setup with address capture and a Check Your Answers (CYA) workflow. Fixed a series of web-layer issues to improve stability and user experience across the appeals workflow.
May 2025 performance summary for Planning-Inspectorate/appeals-back-office. Delivered two major end-to-end features around hearing management and consistently improved reliability through UI/UX tweaks and robust error handling. Implemented a new data model and API layer to support hearing estimates, and established a structured hearing details setup with address capture and a Check Your Answers (CYA) workflow. Fixed a series of web-layer issues to improve stability and user experience across the appeals workflow.
April 2025 delivered major front-end improvements to the appeals back-office: hearing scheduling flows, LPA management UI, and document handling. Key outcomes include a new hearing scheduling journey with date/time capture and estimates, cleanup of LPAQ UI to remove irrelevant data and a validated LPA reference-number workflow with audit logging, and an enhanced document renaming/upload UX with robust input validation. These changes reduce user friction, improve data quality, and establish consistent UI patterns and validation across modules.
April 2025 delivered major front-end improvements to the appeals back-office: hearing scheduling flows, LPA management UI, and document handling. Key outcomes include a new hearing scheduling journey with date/time capture and estimates, cleanup of LPAQ UI to remove irrelevant data and a validated LPA reference-number workflow with audit logging, and an enhanced document renaming/upload UX with robust input validation. These changes reduce user friction, improve data quality, and establish consistent UI patterns and validation across modules.
March 2025 monthly summary for Planning-Inspectorate/appeals-back-office: Delivered targeted enhancements to improve LPAs' communications and data integrity. Implemented Local Planning Authority (LPA) email inclusion in appeal contact details payload and UI, enabling direct, reliable notifications and faster case handling. Fixed a bug in final comments flow to hide deleted attachments on the check-your-answers page, preventing confusion and ensuring accurate document sets. These changes reduce manual follow-ups, improve data quality, and strengthen end-to-end appeal processing. Technologies demonstrated include frontend-backend integration, payload shaping, and UI data filtering, with commit-level traceability via described commits.
March 2025 monthly summary for Planning-Inspectorate/appeals-back-office: Delivered targeted enhancements to improve LPAs' communications and data integrity. Implemented Local Planning Authority (LPA) email inclusion in appeal contact details payload and UI, enabling direct, reliable notifications and faster case handling. Fixed a bug in final comments flow to hide deleted attachments on the check-your-answers page, preventing confusion and ensuring accurate document sets. These changes reduce manual follow-ups, improve data quality, and strengthen end-to-end appeal processing. Technologies demonstrated include frontend-backend integration, payload shaping, and UI data filtering, with commit-level traceability via described commits.
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