compliance-privacy-reviewer

SkillDev tools

Reviews how a feature or system handles PII, data retention, and consent against common privacy-framework principles (GDPR-style). Use when a feature collects, stores, or processes personal data - not a substitute for legal advice.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the compliance-privacy-reviewer skill

What this skill tells your AI

The instructions your AI receives, as published by codebygarv/ai-skills in skills/security/compliance-privacy-reviewer/SKILL.md and read by ahel’s review.

Purpose

Review how a feature collects, stores, processes, and retains personal data against common privacy-framework principles — data minimization, purpose limitation, consent, retention limits, and user rights (access/deletion/export) — flagging gaps before they become compliance problems.

When to Use

  • A feature collects, stores, or processes personal data (PII) — user profiles, tracking/analytics, location data, health/financial data, anything third-party-shareable.
  • Reviewing a data flow or new integration for privacy implications.
  • Before shipping something that touches user data in a new way.

This is not legal advice. Real compliance sign-off (GDPR, CCPA, HIPAA, etc.) requires qualified legal review — this skill flags likely gaps for a human/legal team to evaluate, not a compliance certification.

What to Analyze

  1. Data minimization — is every piece of personal data collected actually necessary for the stated purpose, or is more being collected "just in case"?
  2. Purpose limitation — is data used only for the purpose it was collected for, or silently reused elsewhere (e.g. support-ticket data later used for marketing without new consent)?
  3. Consent — is consent captured before data collection where required, is it specific (not bundled into an unrelated ToS acceptance), and can it be withdrawn?
  4. Retention — is there a defined retention period, or does data accumulate indefinitely with no deletion policy?
  5. User rights — can a user actually access, export, or delete their data on request, or does the current design make that operationally difficult (data scattered across systems with no way to locate/purge it all)?
  6. Third-party sharing — is personal data sent to third parties (analytics, ad tech, subprocessors) disclosed, and is there a data processing agreement consideration flagged for legal?

Output Format

  • Findings grouped by principle (Data Minimization, Purpose Limitation, Consent, Retention, User Rights, Third-Party Sharing).
  • Each finding: what's collected/done, the gap against the principle, and a concrete recommendation.
  • Explicit reminder at the top and bottom of output: this is a technical/design review, not legal sign-off — flag for legal/compliance review before treating any framework as "satisfied."

Avoid

  • Presenting findings as definitive legal compliance verdicts ("this satisfies GDPR") — always frame as "gaps to review with legal," not certification.
  • Assuming a specific jurisdiction's rules apply without being told — different frameworks (GDPR/CCPA/HIPAA/etc.) have different specific requirements; flag general principles common across most of them unless a specific framework is named.
  • Recommending data collection be removed outright when the real fix might be better consent/retention practices — distinguish "don't collect this" from "collect it but handle it properly."

Signals

GitHub stars
25
Forks
1
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
compliance-privacy-reviewer
Source
github.com/codebygarv/ai-skills