AGENT SKILL

privacy-data-handling

Defines how personal data is retained, accessed and deleted. Use when setting up or auditing data handling.

适用职业数据分析师
License 许可
MIT
所属仓库
vibbs/company-os
最近更新
2026-10-21
Stars
★ 6
Forks
2

01 前言 Front Matter

name
privacy-data-handling
runtimes
{ "claude": { "user-invocable": true } }
description
Defines how personal data is retained, accessed and deleted. Use when setting up or auditing data handling.

02 资源文件 2

03 SKILL.md 正文

Privacy & Data Handling

Reference

  • ID: S-RISK-02
  • Category: Risk
  • Inputs: data inventory, regulatory requirements (GDPR, CCPA), system architecture
  • Outputs: data handling policy document → artifacts/risk/
  • Used by: Ops & Risk Agent
  • Tool scripts: ./tools/artifact/validate.sh

Purpose

Establishes clear policies for data retention, access controls, and deletion procedures that comply with privacy regulations and protect user data throughout its lifecycle from collection to destruction.

Procedure

Step 0: Identify Data Processors

Read company.config.yaml and extract third-party data processors:

  • analytics.provider (e.g., PostHog, Mixpanel, Plausible)
  • email.provider (e.g., Resend, SendGrid, Postmark)
  • observability.error_tracking (e.g., Sentry, Datadog)
  • ai.llm_provider (e.g., Anthropic, OpenAI)
  • support.platform (e.g., Intercom, Crisp)

For each identified processor, add a specific line to the DPA (Data Processing Agreement) checklist:

  • [ ] DPA signed with [provider]
  • [ ] Data residency confirmed (EU/US)
  • [ ] Sub-processor list reviewed
  • [ ] Deletion/export API documented
  1. Inventory all personal and sensitive data collected: what data, where stored, why collected.
  2. Classify data by sensitivity level: public, internal, confidential, restricted.
  3. Define retention periods for each data category based on business need and regulatory requirements.
  4. Design access control policies: who can access what data, under what conditions, with what audit trail.
  5. Define the data deletion procedure: user-initiated deletion, retention-based expiry, right-to-be-forgotten flows.
  6. Document data processing lawful bases (consent, legitimate interest, contractual necessity).
  7. Define data breach notification procedures: detection, assessment, notification timeline.
  8. Design audit logging for all data access and modifications.
  9. Map data flows to third-party processors and define DPA requirements.
  10. Save the data handling policy to artifacts/risk/.
  11. Validate the artifact using ./tools/artifact/validate.sh.

Quality Checklist

  • [ ] All personal data fields are inventoried
  • [ ] Data classification levels are assigned
  • [ ] Retention periods are defined and justified
  • [ ] Access controls follow principle of least privilege
  • [ ] Deletion procedures cover all storage locations (DB, backups, caches, logs)
  • [ ] Breach notification timeline meets regulatory requirements
  • [ ] Third-party data processors are documented with DPAs
  • [ ] Artifact passes validation

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