安全

privacy-engineering

Translates privacy principles and legal requirements into data-flow maps, lifecycle records, verifiable acceptance criteria, retention and deletion plans, consent controls, and privacy change reviews.

★ 88 GitHub Stars
95 质量评分
9 文件

关于此 Skill

Translate privacy principles and legal requirements into data-flow, lifecycle, acceptance, and verification artifacts. Map data classification, purpose, processing, access, retention, deletion, residency, and consent; define verifiable privacy acceptance criteria; and produce data-lifecycle records, retention/deletion verification plans, and privacy change reviews. Use when engineering privacy into a system, feature, or data flow — not for legal advice, jurisdiction-specific regulatory interpretation, or replacing security engineering or incident response.

使用场景

  • Mapping data flows, access, residency, and tenant boundaries
  • Creating data-lifecycle records from collection through deletion
  • Defining testable privacy acceptance criteria
  • Planning retention and deletion verification
  • Reviewing privacy impacts of system or feature changes

功能

  • Structured coverage of purpose, lifecycle, access, deletion, isolation, residency, and consent
  • Templates for data flows, lifecycle records, acceptance criteria, and change reviews
  • Retention and deletion verification planning with measurable conditions
  • Guidance for privacy controls on agent traces and analytics telemetry
  • Explicit boundaries from legal advice, security implementation, and incident response

支持的 Agent

未指定

Skill 文件

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