data-retention-policy-checker

When to invoke

• You are drafting or reviewing a data retention policy / schedule.
• You need a quick gap analysis before legal/security review.

Inputs needed

• A JSON policy with:
  • datasets (name, data_class, system, retention_days, deletion_method)
  • legal_hold_supported (bool)
  • backup_retention_days (int)
  • notes (optional)

Workflow

1. Validate schema and required fields.
2. Flag missing or inconsistent retention values.
3. Check for common high-risk patterns:
   • indefinite retention for personal data without justification
   • missing deletion method
   • backup retention longer than primary without rationale
   • no legal hold process
4. Output a human-readable report (Markdown) plus a machine-readable summary section.

Output format

• Summary (counts by severity)
• Findings table (severity, dataset, issue, recommendation)
• Notes and assumptions

Guardrails

• This is not legal advice; report must say it is a preliminary check.
• Do not claim compliance with any specific regulation.

Reference code

• check_retention_policy.py

  reads JSON policy and writes Markdown findings.