gdpr-data-handling
Install this skill
npx skills add wshobson/agentsWorks across Claude Code, Cursor, Codex, Copilot & Antigravity
The gdpr-data-handling skill provides an architectural framework for integrating General Data Protection Regulation requirements directly into application logic. Instead of treating privacy as a secondary administrative layer, this skill embeds consent tracking, audit logging, and data subject rights management into the database schema and service layer. It centers on managing specific data categories—from basic identifiers to sensitive Article 9 health information—while maintaining a verifiable trail of legal bases for processing. By automating the capture of user intent, source context, and policy versions, the system creates a technical audit trail necessary for compliance reporting. This agentic skill assists in constructing front-end consent interfaces and back-end logic that ensures software architectures remain compliant with EU regulatory requirements throughout the data lifecycle.
When to Use This Skill
- •Building consent collection banners that synchronize with back-end database preferences
- •Restricting data processing flows based on dynamic user consent history
- •Generating audit logs for proving user consent to regulatory auditors
- •Configuring data erasure routines to fulfill Article 17 requests
How to Invoke This Skill
Example prompts that trigger this skill in Claude Code, Cursor, or Antigravity:
- “Implement a GDPR-compliant consent flow for my application
- “How should I structure my database to track user consent versions?
- “Generate a class for managing data subject access requests
- “Show me how to verify if a user has consented to marketing analytics
- “Create a model for storing audit trails of user permission changes
Pro Tips
- 💡Always map your data flows: Understand exactly where personal data enters, resides, and is transmitted within your systems to identify potential GDPR risks.
- 💡Prioritize Data Protection Impact Assessments (DPIAs) for high-risk processing activities to proactively address privacy concerns before deployment.
- 💡Regularly review and update your consent mechanisms and privacy policies to reflect changes in regulations and data processing practices.
What this skill does
- •Implementation of consent management storage schemas for tracking granular user permissions
- •Automated recording of policy versions, timestamps, and IP metadata for audit verification
- •Logic gating for checking active consent status before processing specific data purposes
- •Structure for managing and fulfilling data subject access and erasure requests
- •Categorization mapping for standard, sensitive, and children's data types
When not to use it
- ✕When your application processes no personal data from residents of the European Union
- ✕As a substitute for professional legal counsel or formal data protection impact assessments
Example workflow
- Define the required processing purposes and data categories for your system
- Integrate the consent schema into your primary database architecture
- Deploy the ConsentManager class to handle recording and verifying permissions
- Hook the consent-changed events into your downstream data processing microservices
- Implement the front-end consent UI to capture and submit user preferences
Prerequisites
- –An existing database for persistence (e.g., MongoDB, PostgreSQL)
- –A defined privacy policy document for version tracking
Pitfalls & limitations
- !Assuming that technical implementation replaces the need for organizational legal compliance
- !Failing to update consent records when the underlying privacy policy version changes
- !Neglecting to synchronize consent status across distributed service caches
FAQ
How it compares
Unlike manual ad-hoc logging, this skill forces a strict schema for consent tracking, ensuring that audit trails are consistently structured and programmatically verifiable.
📄 Full skill instructions — original source: wshobson/agents
Practical implementation guide for GDPR-compliant data processing, consent management, and privacy controls.
## When to Use This Skill
- Building systems that process EU personal data
- Implementing consent management
- Handling data subject requests (DSRs)
- Conducting GDPR compliance reviews
- Designing privacy-first architectures
- Creating data processing agreements
## Core Concepts
### 1. Personal Data Categories
| Category | Examples | Protection Level |
| ---------------------- | --------------------------- | ------------------ |
| **Basic** | Name, email, phone | Standard |
| **Sensitive (Art. 9)** | Health, religion, ethnicity | Explicit consent |
| **Criminal (Art. 10)** | Convictions, offenses | Official authority |
| **Children's** | Under 16 data | Parental consent |
### 2. Legal Bases for Processing
Article 6 - Lawful Bases:
├── Consent: Freely given, specific, informed
├── Contract: Necessary for contract performance
├── Legal Obligation: Required by law
├── Vital Interests: Protecting someone's life
├── Public Interest: Official functions
└── Legitimate Interest: Balanced against rights### 3. Data Subject Rights
Right to Access (Art. 15) ─┐
Right to Rectification (Art. 16) │
Right to Erasure (Art. 17) │ Must respond
Right to Restrict (Art. 18) │ within 1 month
Right to Portability (Art. 20) │
Right to Object (Art. 21) ─┘## Implementation Patterns
### Pattern 1: Consent Management
// Consent data model
const consentSchema = {
userId: String,
consents: [
{
purpose: String, // 'marketing', 'analytics', etc.
granted: Boolean,
timestamp: Date,
source: String, // 'web_form', 'api', etc.
version: String, // Privacy policy version
ipAddress: String, // For proof
userAgent: String, // For proof
},
],
auditLog: [
{
action: String, // 'granted', 'withdrawn', 'updated'
purpose: String,
timestamp: Date,
source: String,
},
],
};
// Consent service
class ConsentManager {
async recordConsent(userId, purpose, granted, metadata) {
const consent = {
purpose,
granted,
timestamp: new Date(),
source: metadata.source,
version: await this.getCurrentPolicyVersion(),
ipAddress: metadata.ipAddress,
userAgent: metadata.userAgent,
};
// Store consent
await this.db.consents.updateOne(
{ userId },
{
$push: {
consents: consent,
auditLog: {
action: granted ? "granted" : "withdrawn",
purpose,
timestamp: consent.timestamp,
source: metadata.source,
},
},
},
{ upsert: true },
);
// Emit event for downstream systems
await this.eventBus.emit("consent.changed", {
userId,
purpose,
granted,
timestamp: consent.timestamp,
});
}
async hasConsent(userId, purpose) {
const record = await this.db.consents.findOne({ userId });
if (!record) return false;
const latestConsent = record.consents
.filter((c) => c.purpose === purpose)
.sort((a, b) => b.timestamp - a.timestamp)[0];
return latestConsent?.granted === true;
}
async getConsentHistory(userId) {
const record = await this.db.consents.findOne({ userId });
return record?.auditLog || [];
}
}<!-- GDPR-compliant consent UI -->
<div class="consent-banner" role="dialog" aria-labelledby="consent-title">
<h2 id="consent-title">Cookie Preferences</h2>
<p>
We use cookies to improve your experience. Select your preferences below.
</p>
<form id="consent-form">
<!-- Necessary - always on, no consent needed -->
<div class="consent-category">
<input type="checkbox" id="necessary" checked disabled />
<label for="necessary">
<strong>Necessary</strong>
<span>Required for the website to function. Cannot be disabled.</span>
</label>
</div>
<!-- Analytics - requires consent -->
<div class="consent-category">
<input type="checkbox" id="analytics" name="analytics" />
<label for="analytics">
<strong>Analytics</strong>
<span>Help us understand how you use our site.</span>
</label>
</div>
<!-- Marketing - requires consent -->
<div class="consent-category">
<input type="checkbox" id="marketing" name="marketing" />
<label for="marketing">
<strong>Marketing</strong>
<span>Personalized ads based on your interests.</span>
</label>
</div>
<div class="consent-actions">
<button type="button" id="accept-all">Accept All</button>
<button type="button" id="reject-all">Reject All</button>
<button type="submit">Save Preferences</button>
</div>
<p class="consent-links">
<a href="/privacy-policy">Privacy Policy</a> |
<a href="/cookie-policy">Cookie Policy</a>
</p>
</form>
</div>### Pattern 2: Data Subject Access Request (DSAR)
from datetime import datetime, timedelta
from typing import Dict, List, Optional
import json
class DSARHandler:
"""Handle Data Subject Access Requests."""
RESPONSE_DEADLINE_DAYS = 30
EXTENSION_ALLOWED_DAYS = 60 # For complex requests
def __init__(self, data_sources: List['DataSource']):
self.data_sources = data_sources
async def submit_request(
self,
request_type: str, # 'access', 'erasure', 'rectification', 'portability'
user_id: str,
verified: bool,
details: Optional[Dict] = None
) -> str:
"""Submit a new DSAR."""
request = {
'id': self.generate_request_id(),
'type': request_type,
'user_id': user_id,
'status': 'pending_verification' if not verified else 'processing',
'submitted_at': datetime.utcnow(),
'deadline': datetime.utcnow() + timedelta(days=self.RESPONSE_DEADLINE_DAYS),
'details': details or {},
'audit_log': [{
'action': 'submitted',
'timestamp': datetime.utcnow(),
'details': 'Request received'
}]
}
await self.db.dsar_requests.insert_one(request)
await self.notify_dpo(request)
return request['id']
async def process_access_request(self, request_id: str) -> Dict:
"""Process a data access request."""
request = await self.get_request(request_id)
if request['type'] != 'access':
raise ValueError("Not an access request")
# Collect data from all sources
user_data = {}
for source in self.data_sources:
try:
data = await source.get_user_data(request['user_id'])
user_data[source.name] = data
except Exception as e:
user_data[source.name] = {'error': str(e)}
# Format response
response = {
'request_id': request_id,
'generated_at': datetime.utcnow().isoformat(),
'data_categories': list(user_data.keys()),
'data': user_data,
'retention_info': await self.get_retention_info(),
'processing_purposes': await self.get_processing_purposes(),
'third_party_recipients': await self.get_recipients()
}
# Update request status
await self.update_request(request_id, 'completed', response)
return response
async def process_erasure_request(self, request_id: str) -> Dict:
"""Process a right to erasure request."""
request = await self.get_request(request_id)
if request['type'] != 'erasure':
raise ValueError("Not an erasure request")
results = {}
exceptions = []
for source in self.data_sources:
try:
# Check for legal exceptions
can_delete, reason = await source.can_delete(request['user_id'])
if can_delete:
await source.delete_user_data(request['user_id'])
results[source.name] = 'deleted'
else:
exceptions.append({
'source': source.name,
'reason': reason # e.g., 'legal retention requirement'
})
results[source.name] = f'retained: {reason}'
except Exception as e:
results[source.name] = f'error: {str(e)}'
response = {
'request_id': request_id,
'completed_at': datetime.utcnow().isoformat(),
'results': results,
'exceptions': exceptions
}
await self.update_request(request_id, 'completed', response)
return response
async def process_portability_request(self, request_id: str) -> bytes:
"""Generate portable data export."""
request = await self.get_request(request_id)
user_data = await self.process_access_request(request_id)
# Convert to machine-readable format (JSON)
portable_data = {
'export_date': datetime.utcnow().isoformat(),
'format_version': '1.0',
'data': user_data['data']
}
return json.dumps(portable_data, indent=2, default=str).encode()### Pattern 3: Data Retention
from datetime import datetime, timedelta
from enum import Enum
class RetentionBasis(Enum):
CONSENT = "consent"
CONTRACT = "contract"
LEGAL_OBLIGATION = "legal_obligation"
LEGITIMATE_INTEREST = "legitimate_interest"
class DataRetentionPolicy:
"""Define and enforce data retention policies."""
POLICIES = {
'user_account': {
'retention_period_days': 365 * 3, # 3 years after last activity
'basis': RetentionBasis.CONTRACT,
'trigger': 'last_activity_date',
'archive_before_delete': True
},
'transaction_records': {
'retention_period_days': 365 * 7, # 7 years for tax
'basis': RetentionBasis.LEGAL_OBLIGATION,
'trigger': 'transaction_date',
'archive_before_delete': True,
'legal_reference': 'Tax regulations require 7 year retention'
},
'marketing_consent': {
'retention_period_days': 365 * 2, # 2 years
'basis': RetentionBasis.CONSENT,
'trigger': 'consent_date',
'archive_before_delete': False
},
'support_tickets': {
'retention_period_days': 365 * 2,
'basis': RetentionBasis.LEGITIMATE_INTEREST,
'trigger': 'ticket_closed_date',
'archive_before_delete': True
},
'analytics_data': {
'retention_period_days': 365, # 1 year
'basis': RetentionBasis.CONSENT,
'trigger': 'collection_date',
'archive_before_delete': False,
'anonymize_instead': True
}
}
async def apply_retention_policies(self):
"""Run retention policy enforcement."""
for data_type, policy in self.POLICIES.items():
cutoff_date = datetime.utcnow() - timedelta(
days=policy['retention_period_days']
)
if policy.get('anonymize_instead'):
await self.anonymize_old_data(data_type, cutoff_date)
else:
if policy.get('archive_before_delete'):
await self.archive_data(data_type, cutoff_date)
await self.delete_old_data(data_type, cutoff_date)
await self.log_retention_action(data_type, cutoff_date)
async def anonymize_old_data(self, data_type: str, before_date: datetime):
"""Anonymize data instead of deleting."""
# Example: Replace identifying fields with hashes
if data_type == 'analytics_data':
await self.db.analytics.update_many(
{'collection_date': {'$lt': before_date}},
{'$set': {
'user_id': None,
'ip_address': None,
'device_id': None,
'anonymized': True,
'anonymized_date': datetime.utcnow()
}}
)### Pattern 4: Privacy by Design
class PrivacyFirstDataModel:
"""Example of privacy-by-design data model."""
# Separate PII from behavioral data
user_profile_schema = {
'user_id': str, # UUID, not sequential
'email_hash': str, # Hashed for lookups
'created_at': datetime,
# Minimal data collection
'preferences': {
'language': str,
'timezone': str
}
}
# Encrypted at rest
user_pii_schema = {
'user_id': str,
'email': str, # Encrypted
'name': str, # Encrypted
'phone': str, # Encrypted (optional)
'address': dict, # Encrypted (optional)
'encryption_key_id': str
}
# Pseudonymized behavioral data
analytics_schema = {
'session_id': str, # Not linked to user_id
'pseudonym_id': str, # Rotating pseudonym
'events': list,
'device_category': str, # Generalized, not specific
'country': str, # Not city-level
}
class DataMinimization:
"""Implement data minimization principles."""
@staticmethod
def collect_only_needed(form_data: dict, purpose: str) -> dict:
"""Filter form data to only fields needed for purpose."""
REQUIRED_FIELDS = {
'account_creation': ['email', 'password'],
'newsletter': ['email'],
'purchase': ['email', 'name', 'address', 'payment'],
'support': ['email', 'message']
}
allowed = REQUIRED_FIELDS.get(purpose, [])
return {k: v for k, v in form_data.items() if k in allowed}
@staticmethod
def generalize_location(ip_address: str) -> str:
"""Generalize IP to country level only."""
import geoip2.database
reader = geoip2.database.Reader('GeoLite2-Country.mmdb')
try:
response = reader.country(ip_address)
return response.country.iso_code
except:
return 'UNKNOWN'### Pattern 5: Breach Notification
from datetime import datetime
from enum import Enum
class BreachSeverity(Enum):
LOW = "low"
MEDIUM = "medium"
HIGH = "high"
CRITICAL = "critical"
class BreachNotificationHandler:
"""Handle GDPR breach notification requirements."""
AUTHORITY_NOTIFICATION_HOURS = 72
AFFECTED_NOTIFICATION_REQUIRED_SEVERITY = BreachSeverity.HIGH
async def report_breach(
self,
description: str,
data_types: List[str],
affected_count: int,
severity: BreachSeverity
) -> dict:
"""Report and handle a data breach."""
breach = {
'id': self.generate_breach_id(),
'reported_at': datetime.utcnow(),
'description': description,
'data_types_affected': data_types,
'affected_individuals_count': affected_count,
'severity': severity.value,
'status': 'investigating',
'timeline': [{
'event': 'breach_reported',
'timestamp': datetime.utcnow(),
'details': description
}]
}
await self.db.breaches.insert_one(breach)
# Immediate notifications
await self.notify_dpo(breach)
await self.notify_security_team(breach)
# Authority notification required within 72 hours
if self.requires_authority_notification(severity, data_types):
breach['authority_notification_deadline'] = (
datetime.utcnow() + timedelta(hours=self.AUTHORITY_NOTIFICATION_HOURS)
)
await self.schedule_authority_notification(breach)
# Affected individuals notification
if severity.value in [BreachSeverity.HIGH.value, BreachSeverity.CRITICAL.value]:
await self.schedule_individual_notifications(breach)
return breach
def requires_authority_notification(
self,
severity: BreachSeverity,
data_types: List[str]
) -> bool:
"""Determine if supervisory authority must be notified."""
# Always notify for sensitive data
sensitive_types = ['health', 'financial', 'credentials', 'biometric']
if any(t in sensitive_types for t in data_types):
return True
# Notify for medium+ severity
return severity in [BreachSeverity.MEDIUM, BreachSeverity.HIGH, BreachSeverity.CRITICAL]
async def generate_authority_report(self, breach_id: str) -> dict:
"""Generate report for supervisory authority."""
breach = await self.get_breach(breach_id)
return {
'organization': {
'name': self.config.org_name,
'contact': self.config.dpo_contact,
'registration': self.config.registration_number
},
'breach': {
'nature': breach['description'],
'categories_affected': breach['data_types_affected'],
'approximate_number_affected': breach['affected_individuals_count'],
'likely_consequences': self.assess_consequences(breach),
'measures_taken': await self.get_remediation_measures(breach_id),
'measures_proposed': await self.get_proposed_measures(breach_id)
},
'timeline': breach['timeline'],
'submitted_at': datetime.utcnow().isoformat()
}## Compliance Checklist
## GDPR Implementation Checklist
### Legal Basis
- [ ] Documented legal basis for each processing activity
- [ ] Consent mechanisms meet GDPR requirements
- [ ] Legitimate interest assessments completed
### Transparency
- [ ] Privacy policy is clear and accessible
- [ ] Processing purposes clearly stated
- [ ] Data retention periods documented
### Data Subject Rights
- [ ] Access request process implemented
- [ ] Erasure request process implemented
- [ ] Portability export available
- [ ] Rectification process available
- [ ] Response within 30-day deadline
### Security
- [ ] Encryption at rest implemented
- [ ] Encryption in transit (TLS)
- [ ] Access controls in place
- [ ] Audit logging enabled
### Breach Response
- [ ] Breach detection mechanisms
- [ ] 72-hour notification process
- [ ] Breach documentation system
### Documentation
- [ ] Records of processing activities (Art. 30)
- [ ] Data protection impact assessments
- [ ] Data processing agreements with vendors## Best Practices
### Do's
- **Minimize data collection** - Only collect what's needed
- **Document everything** - Processing activities, legal bases
- **Encrypt PII** - At rest and in transit
- **Implement access controls** - Need-to-know basis
- **Regular audits** - Verify compliance continuously
### Don'ts
- **Don't pre-check consent boxes** - Must be opt-in
- **Don't bundle consent** - Separate purposes separately
- **Don't retain indefinitely** - Define and enforce retention
- **Don't ignore DSARs** - 30-day response required
- **Don't transfer without safeguards** - SCCs or adequacy decisions
## Resources
- [GDPR Full Text](https://gdpr-info.eu/)
- [ICO Guidance](https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/)
- [EDPB Guidelines](https://edpb.europa.eu/our-work-tools/general-guidance/gdpr-guidelines-recommendations-best-practices_en)
How to Use This Skill Unit
Option A: Project-Specific (Recommended)
- Click "Download" above
- In your project, create the directory:
.agent/skills/gdpr-data-handling/ - Save the file as
SKILL.md - The agent will automatically discover the skill based on its description.
Option B: Global Installation (All Agents)
Save the file to these locations to make it available across all projects:
- Claude Code:
~/.claude/skills/wshobson/agents/gdpr-data-handling/SKILL.md - Cursor:
~/.cursor/skills/wshobson/agents/gdpr-data-handling/SKILL.md - Antigravity:
~/.gemini/antigravity/skills/wshobson/agents/gdpr-data-handling/SKILL.md
🚀 Install with CLI:npx skills add wshobson/agents