Context

The current design of the Confluence Cloud Migration Assistant (CCMA) pre-migration checks focuses on technical blockers (such as user conflicts or space key overlaps). While the tool is performing as intended, it does not currently provide visibility into the post-migration state of content—specifically regarding Legacy Editor pages that may require manual intervention or layout adjustments in Cloud.

The Opportunity for Improvement

Currently, administrators often discover "broken" pages or layout discrepancies only after the migration is finalized. While there is a [Export List of Legacy Pages and their Eligibility Status | Confluence | Atlassian Support|https://support.atlassian.com/confluence/kb/export-list-of-legacy-pages-and-their-eligibility-status/] to check page eligibility, it is a reactive process that must be performed space-by-space.

Integrating this assessment into the CCMA pre-checks would transform it from a technical validation tool into a comprehensive migration planning assistant.

Suggested Enhancement

Incorporate a "Content Compatibility Assessment" into the CCMA pre-migration phase that:

• Scans for Legacy Content: Automatically identifies pages using the Legacy Editor across all selected spaces.

• Flags High-Risk Pages: Highlights content containing macros or formatting known to have compatibility issues with the Cloud Editor.

• Generates a Planning Report: Provides a downloadable summary (similar to the existing KB report) that admins can use to coordinate with stakeholders before the migration begins.

Value to Customers

• Eliminates "Last-Minute Surprises": Allows admins to identify and fix complex pages before they are migrated, ensuring a smoother transition for end-users.

• Streamlines UAT: Provides a targeted list of pages for User Acceptance Testing, making the validation phase faster and more comprehensive.

• Better Stakeholder Management: Enables administrators to provide clear, data-driven communication to users about which pages might look different post-migration.

• Scalability: Replaces manual, time-consuming workarounds with an automated, site-level assessment.