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Data Retention Policy Change & Deletion Readiness Review
Data Retention Policy Change & Deletion Readiness Review is a bounded ToolForge Labs workflow.
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Data Retention Policy Change & Deletion Readiness Review
Example session with this skill installed
Review a planned change from 24-month to 12-month retention for customer activity data. We have policy text, storage inventories, backup schedules, log/analytics systems, processor contracts, legal-hold notes, and rollout plans. Identify readiness gaps before enforcement.
- Read your context and instructions
- Compiled the data retention policy
The likely issue is a contract mismatch around data retention policy changes, deletion schedules, backups, logs, analytics, legal holds, customer exports, third-party processors, restore behavior, evidence, rollout, rollback limits, and ownership. I would first define the invariant: A retention change is ready only when every covered data copy, exception, hold, processor, restore path, and deletion proof is mapped to an owner and enforceable schedule without silently deleting protected data or retaining expired data. Then I would trace the smallest owning boundary, apply or propose a bounded repair/review step, and add deterministic normal, boundary, failure and replay tests. The workflow preserves existing authorization, privacy, security policy, public interfaces, user-visible behavior, and documented operational ownership. If repository/workspace files are available, findings can be mapped to exact paths and focused local validation; with partial evidence, the result stays an explicit diagnosis/evidence map with assumptions and no invented execution claims.
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About this skill
Data Retention Policy Change & Deletion Readiness Review is a bounded ToolForge Labs workflow. Diagnose, review, and repair data retention policy changes, deletion schedules, backups, logs, analytics, legal holds, customer exports, third-party processors, restore behavior, evidence, rollout, rollback limits, and ownership. Works from repositories/workspaces or partial evidence. Produces bounded fixes or evidence gates with deterministic validation while preserving product/security policy and avoiding invented execution claims. It works from a full repository/workspace or partial evidence such as snippets, logs, configuration, traces, documents, tickets, and architecture notes. The skill separates verified facts from assumptions, avoids invented execution claims, and produces concrete repair/review steps with focused deterministic validation or traceable evidence.
Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for Data & Databases.
Requires repository access or specific configuration/log snippets to be effective. Cannot perform live production database queries or verify actual data deletion in real-time.
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Permissions
Use a clean branch or controlled review workspace. Supply repository/workspace files, logs, traces, configuration, documents, or evidence needed for the task. Review patches/findings before merge or operational action; keep production credentials and destructive production actions out of the workflow.