| name | dataverse-data-operations |
| description | Use when planning Dataverse data quality, duplicate detection, ownership repair, migration, classification, normalization, or bulk data operations. Produces safe operation plans only and performs no data changes. |
Dataverse Data Operations
Purpose
Plan safe AI-assisted data operations for Dataverse environments.
Use this skill for:
- duplicate detection and merge planning
- orphaned or ownerless record repair
- bulk ownership changes
- missing classification or region assignment
- contact/account normalization
- migration readiness and cleanup
- relationship and reference repair
V1 Boundary
This skill does not read or mutate data in Dataverse. It creates operation plans, validation checklists, and implementation guidance.
Workflow
- Identify the target data set, table scope, filters, business unit boundaries, and expected record count.
- Define detection rules for duplicates, invalid references, missing ownership, incomplete classifications, or inconsistent values.
- Require a preview phase that lists selected records, proposed changes, excluded records, and confidence levels.
- Define approval and rollback strategy for every bulk or irreversible change.
- Specify audit fields, evidence records, and before/after reporting.
Output Format
Return:
Operation summary: data issue and desired business outcome.Selection logic: candidate tables, filters, joins, and exclusions.Validation rules: quality checks before changes.Change plan: proposed updates or migration steps.Safety controls: preview, approvals, rollback, and audit.Reporting: before/after metrics and exception handling.
