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 cover
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node --versionimplementing-gdpr-data-protection-controlsExecute the skills CLI command in your project's root directory to begin installation:
Fetches implementing-gdpr-data-protection-controls from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
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Confirm successful installation by checking the skill directory location:
Restart Cursor to activate implementing-gdpr-data-protection-controls. Access via /implementing-gdpr-data-protection-controls in your agent's command palette.
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Generate Python/SQL to fix date formats, impute missing values, remove duplicates
Automate 80% of data preprocessing work
Perform hypothesis testing, regression, and statistical modeling
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Run A/B test analysis, calculate confidence intervals, interpret p-values
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| name | implementing-gdpr-data-protection-controls |
| description | 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 cover |
| domain | cybersecurity |
| subdomain | compliance-governance |
| tags | - compliance - governance - gdpr - privacy - data-protection - eu-regulation |
| nist_csf | - GV.OC-02 - GV.PO-01 - PR.DS-01 - PR.AA-01 - ID.AM-02 |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| nist_ai_rmf | - MEASURE-2.7 - MAP-5.1 - MANAGE-2.4 - MEASURE-2.8 - MEASURE-2.9 |
| atlas_techniques | - AML.T0070 - AML.T0066 - AML.T0082 |
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.
| 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) |
The regulation requires organizations to implement measures appropriate to the risk:
| Right | Article | Description |
|---|---|---|
| Right to be informed | 13-14 | Transparent information about processing |
| Right of access | 15 | Obtain copy of personal data |
| Right to rectification | 16 | Correct inaccurate data |
| Right to erasure | 17 | "Right to be forgotten" |
| Right to restrict processing | 18 | Limit processing of data |
| Right to data portability | 20 | Receive data in machine-readable format |
| Right to object | 21 | Object to processing (especially direct marketing) |
| Automated decision-making | 22 | Not be subject to solely automated decisions |
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Prerequisites
Time Estimate
20-40 minutes to set up and run first analysis
Steps
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✓ Use when
Use for exploratory data analysis, data cleaning, statistical testing, visualization prototyping, and learning new analysis techniques. Best for initial exploration and rapid insights.
✗ Avoid when
Avoid for mission-critical financial analysis, medical research requiring regulatory compliance, production ML models, or when deep statistical expertise is required for nuanced interpretation.
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
Registry listing for implementing-gdpr-data-protection-controls matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: implementing-gdpr-data-protection-controls is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend implementing-gdpr-data-protection-controls for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added implementing-gdpr-data-protection-controls from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
implementing-gdpr-data-protection-controls is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in implementing-gdpr-data-protection-controls — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: implementing-gdpr-data-protection-controls is focused, and the summary matches what you get after install.
Useful defaults in implementing-gdpr-data-protection-controls — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: implementing-gdpr-data-protection-controls is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added implementing-gdpr-data-protection-controls from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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