data-minimization-review

name	data-minimization-review
description	Reduce personal-data collection and persistence to what is necessary for approved product purposes while preserving required functionality and evidence.

Data Minimization Review

Use when this procedure is the primary professional method needed for the assignment.

Procedure

1. Confirm the decision or outcome this work must support, its scope, owner, constraints, and definition of success.
2. Establish the evidence baseline using product requirements, data flow map, analytics needs, support/legal obligations, and current consumers. Do not fill material gaps with assumptions when they can change the result.
3. Challenge each field/event, prefer coarse/derived values where sufficient, shorten retention, remove redundant copies, and test downstream impact.
4. Exercise realistic edge, failure, transition, or exception cases that could invalidate the result; record unresolved uncertainty explicitly.
5. Validate the output against the original outcome and any neighboring professional contracts so this skill does not silently absorb another specialist's authority.
6. Record the resulting artifact, measurements, decisions, provenance, and handoff information needed for another owner to reproduce or continue the work.

Quality gate

Removed or reduced data is proven unnecessary to the approved purpose and no hidden consumer silently recreates it.