gdpr-us-multinational

gdpr-us-multinational is a skill for Claude Code, Codex from vaquarkhan/compliance-agent-skills. It costs 189 tokens per session (2,470 once invoked), scanned A, original, MIT.

A set of workflows for applying the European Union's GDPR privacy law to companies headquartered in the United States. It covers topics such as lawful processing, security, breach reporting, impact assessments, and transfers of data to the US.

In plain words
What is it for?
Use it to assess AI prompts, support data, analytics, subprocessors, international transfers, breach response, and documentation such as records of processing.
Why use it?
It helps identify GDPR duties when a US company offers services to people in Europe or monitors their behaviour. This matters even when the company itself is based outside Europe.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to assess AI prompts, support data, analytics, subprocessors, international transfers, breach response, and documentation such as records of processing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vaquarkhan/compliance-agent-skills/gdpr-us-multinational
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add vaquarkhan/compliance-agent-skills --skill gdpr-us-multinational
Clone the repo
git clone --depth 1 https://github.com/vaquarkhan/compliance-agent-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for gdpr-us-multinational

README.md
[![agentmods](https://agentmods.dev/badge/skills/vaquarkhan/compliance-agent-skills/gdpr-us-multinational/github.svg)](https://agentmods.dev/skills/vaquarkhan/compliance-agent-skills/gdpr-us-multinational)
Your own site
<a href="https://agentmods.dev/skills/vaquarkhan/compliance-agent-skills/gdpr-us-multinational"><img src="https://agentmods.dev/badge/skills/vaquarkhan/compliance-agent-skills/gdpr-us-multinational/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for gdpr-us-multinational

Your own site · 80×15
<a href="https://agentmods.dev/skills/vaquarkhan/compliance-agent-skills/gdpr-us-multinational"><img src="https://agentmods.dev/badge/skills/vaquarkhan/compliance-agent-skills/gdpr-us-multinational.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 189 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,470 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00189 $0.02470
Opus 5 $0.00095 $0.01235
Sonnet 5 $0.00038 $0.00494
Haiku 4.5 $0.00019 $0.00247

Measured 11d ago against content hash ef33c39b2358, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

gdpr-us-multinational scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/gdpr-us-multinational/SKILL.md · 180 lines

How it starts

The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GDPR for US Multinationals

Overview

General Data Protection Regulation (EU) 2016/679 applies to US companies when they offer goods/services to EU/EEA data subjects or monitor their behavior—regardless of US headquarters. Agent/LLM systems processing EU user prompts, support chat, or analytics fall in scope.

GDPR topic Article US multinational focus
Principles Art. 5 Lawfulness, minimization, storage limitation for agent logs
Lawful basis Art. 6 Consent vs legitimate interest for AI features
Special categories Art. 9 Health, biometric in prompts—explicit consent or Art. 9(2) exception
Records of processing Art. 30 RoPA must list LLM/MCP subprocessors and transfers
Security Art. 32 Encryption, redaction gate, MCP access controls
Breach notification Art. 33-34 72 hours to supervisory authority; data subject notice if high risk
DPIA Art. 35 Required for systematic profiling, large-scale special categories
Transfers Art. 44-49 SCCs, DPF, or adequacy for US LLM processing
DPO Art. 37-39 Required for large-scale special category or systematic monitoring
Rights Art. 15-22 Access, erasure, portability—LLM vendor deletion complexity

Transfer mechanisms (2024+):

  • EU-US Data Privacy Framework (DPF) — US entities self-certify; verify LLM vendor DPF status
  • Standard Contractual Clauses (2021 SCCs) — Module 2 controller-processor for LLM vendors
  • UK IDTA / Addendum — if UK data subjects included

Reference: references/gdpr-article-checklist.md, template templates/gdpr-ropa-template.yaml

When to Use

Use this skill when:

  • US company processes EU/EEA (or UK) residents' personal data in products or agents
  • Assessing cross-border transfers to US-based LLM APIs (OpenAI, Anthropic, etc.)
  • Building Article 30 RoPA including agent/MCP processing activities
  • DPIA for agent profiling, automated decisions, or health-related prompts
  • 72-hour breach notification to lead supervisory authority (cross-border one-stop-shop)
  • Drafting DPA/SCCs with LLM and MCP subprocessors
  • DPO consultation on high-risk AI agent deployment in EU market

Read the full file on GitHub · 180 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 180 lines · 189 tokens per session scan A ef33c39b2358

Subscribe to this mod's changes

gdpr-us-multinational is a skill published in the GitHub repository vaquarkhan/compliance-agent-skills (2 stars, last pushed 17d ago), licensed MIT. It adds 189 tokens to every session and 2,470 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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