implementing-gdpr-data-protection-controls

implementing-gdpr-data-protection-controls is a skill for Claude Code, Codex from adriannoes/awesome-agentic-ai. It costs 52 tokens per session (1,860 once invoked), scanned A, a copy of implementing-gdpr-data-protection-controls, MIT.

A guide to applying the General Data Protection Regulation, the European Union law governing personal-data collection and use. It covers technical controls and organizational processes for protecting that data.

In plain words
What is it for?
Use it to create data-protection measures, conduct Data Protection Impact Assessments, manage privacy requests, plan breach notifications, and document cross-border data flows.
Why use it?
It helps organizations handle privacy responsibilities systematically instead of treating them as isolated technical tasks. The work includes assessing risks, responding to data-subject requests, reporting breaches, and managing international transfers.

Skill for Claude CodeCodex

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

Good fit Use it to create data-protection measures, conduct Data Protection Impact Assessments, manage privacy requests, plan breach notifications, and document cross-border data flows.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/adriannoes/awesome-agentic-ai/implementing-gdpr-data-protection-controls
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 adriannoes/awesome-agentic-ai --skill implementing-gdpr-data-protection-controls
Clone the repo
git clone --depth 1 https://github.com/adriannoes/awesome-agentic-ai

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 implementing-gdpr-data-protection-controls

README.md
[![agentmods](https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/implementing-gdpr-data-protection-controls/github.svg)](https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/implementing-gdpr-data-protection-controls)
Your own site
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/implementing-gdpr-data-protection-controls"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/implementing-gdpr-data-protection-controls/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 implementing-gdpr-data-protection-controls

Your own site · 80×15
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/implementing-gdpr-data-protection-controls"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/implementing-gdpr-data-protection-controls.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,860 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 92% copy Near-identical to another mod 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 $0.00052 $0.01860
Opus 5 $0.00026 $0.00930
Sonnet 5 $0.00010 $0.00372
Haiku 4.5 $0.00005 $0.00186

Measured 7d ago against content hash 0c74694af7cd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

implementing-gdpr-data-protection-controls 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 7d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/agent.py, scripts/process.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

92% identical to implementing-gdpr-data-protection-controls — 32 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

cursor-claude-codex/skills/anthropic-cybersecurity-skills/skills/implementing-gdpr-data-protection-controls/SKILL.md · 197 lines

How it starts

The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Implementing GDPR Data Protection Controls

Overview

The General Data Protection Regulation (EU) 2016/679 (GDPR) is the EU's comprehensive data protection law governing the collection, processing, storage, and transfer of personal data. This skill covers implementing the technical and organizational measures required by GDPR, including data protection by design and by default, Data Protection Impact Assessments (DPIAs), data subject rights management, breach notification procedures, and cross-border data transfer mechanisms.

When to Use

  • When deploying or configuring implementing gdpr data protection controls capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Prerequisites

  • Understanding of EU data protection law and its territorial scope
  • Knowledge of personal data processing activities within the organization
  • Familiarity with data architecture, databases, and application systems
  • Understanding of data flows including cross-border transfers

Core Concepts

Key GDPR Articles for Technical Controls

Article Requirement
Art. 5 Principles: lawfulness, purpose limitation, data minimization, accuracy, storage limitation, integrity and confidentiality, accountability
Art. 6 Lawful basis for processing (consent, contract, legal obligation, vital interests, public task, legitimate interest)
Art. 25 Data protection by design and by default
Art. 28 Processor obligations and contractual requirements
Art. 30 Records of processing activities (ROPA)
Art. 32 Security of processing (technical and organizational measures)
Art. 33 Breach notification to supervisory authority (72 hours)
Art. 34 Communication of breach to data subjects
Art. 35 Data Protection Impact Assessment (DPIA)
Art. 37-39 Data Protection Officer (DPO) appointment and role
Art. 44-49 Cross-border data transfers (adequacy, SCCs, BCRs)

Read the full file on GitHub · 197 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 7d ago First seen · 197 lines · 52 tokens per session scan A 0c74694af7cd

Subscribe to this mod's changes

implementing-gdpr-data-protection-controls is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 13d ago), licensed MIT. It adds 52 tokens to every session and 1,860 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to implementing-gdpr-data-protection-controls, differing in 32 lines, and is treated as a copy.

Related

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implementing-gdpr-data-protection-controls

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