agentic-security:privacy-data-flow

Classify PII/PHI/PCI data flows and write DATA_FLOW.md artifacts.

73|15|Updated May 6, 2026
One-click install
npx skills add https://github.com/Clear-Capabilities/agentic-security --skill agentic-security-privacy-data-flow
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: agentic-security:privacy-data-flow
Source: https://github.com/Clear-Capabilities/agentic-security/tree/main/skills/privacy-data-flow
Command: npx skills add https://github.com/Clear-Capabilities/agentic-security --skill agentic-security-privacy-data-flow

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Privacy review before handling user data. Activate on PII/PHI/PCI shapes (email, SSN, CC, MRN). Writes DATA_FLOW.md.

Core Features & Use Cases

  • Pause before data-handling edits to surface privacy risks early.
  • Classify touched data (PII/PHI/PCI) and map destinations (storage, transit, logs, backups).
  • Use during code reviews, PRs, and architecture changes affecting data flows.

Quick Start

Run a privacy data-flow review before editing code that processes user data.

Frequently Asked Questions about agentic-security:privacy-data-flow

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify privacy risks in code paths that process PII and PHI?

To identify privacy risks in PII and PHI code paths, you need to map data-flow destinations across storage, transit, and logs. This Skill classifies touched data and generates a DATA_FLOW.md artifact to surface privacy review risks early.

When do I need to perform a privacy data-flow review for PCI data?

A privacy data-flow review for PCI data is needed during code reviews, PRs, and architecture changes affecting data flows. It pre-validates data handling across backups and retention policies before edits are applied.

How do I map data classification and flow for jurisdiction considerations?

Map data classification and flow for jurisdiction considerations by classifying how user data moves through code paths that read, store, or transmit PII/PHI/PCI. This produces concrete guidance encoded in a DATA_FLOW.md artifact.

Does this privacy review approach work for third-party processor changes?

Yes, privacy review works for third-party processor changes by analyzing how user data transits to external services. It maps these data-flow destinations to satisfy privacy review criteria and surface compliance risks.

What is the best way to pre-validate privacy before handling user data?

The best way to pre-validate privacy before handling user data is to pause before data-handling edits to classify touched data and map destinations. This generates a DATA_FLOW.md artifact capturing retention and flow risks.