Comprehensive guidance for implementing data privacy compliance across GDPR, CCPA, HIPAA, and other global data protection regulations.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondata-privacy-complianceExecute the skills CLI command in your project's root directory to begin installation:
Fetches data-privacy-compliance from davila7/claude-code-templates and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate data-privacy-compliance. Access via /data-privacy-compliance in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Comprehensive guidance for implementing data privacy compliance across GDPR, CCPA, HIPAA, and other global data protection regulations.
Use this skill when:
Scope: EU residents' data, regardless of where company is located Key Requirements:
Penalties: Up to €20M or 4% of global annual revenue
Scope: California residents' data Key Requirements:
Penalties: Up to $7,500 per intentional violation
Scope: Protected Health Information (PHI) in the US Key Requirements:
Penalties: Up to $1.5M per violation category per year
Request Handler:
async function handleAccessRequest(userId, email) {
// Verify identity
const verified = await verifyIdentity(email);
if (!verified) throw new Error('Identity verification failed');
// Collect all personal data
const userData = await collectUserData(userId);
// Format for readability
const report = {
personalInfo: userData.profile,
activityLogs: userData.activities,
preferences: userData.settings,
thirdPartySharing: userData.dataSharing,
retentionPeriod: '2 years from last activity',
dataProtectionOfficer: '[email protected]'
};
// Generate downloadable report
const pdf = await generatePDFReport(report);
// Log request for compliance
await logAccessRequest(userId, 'completed');
return pdf;
}
Response Timeline:
Deletion Handler:
async function handleDeletionRequest(userId, email) {
// Verify identity
const verified = await verifyIdentity(email);
if (!verified) throw new Error('Identity verification failed');
// Check for legal obligations to retain
const mustRetain = await checkRetentionRequirements(userId);
if (mustRetain.required) {
return {
status: 'partial_deletion',
retained: mustRetain.data,
reason: mustRetain.legalBasis,
retentionPeriod: mustRetain.period
};
}
// Delete from all systems
await Promise.all([
deleteFromDatabase(userId),
deleteFromBackups(userId), // Mark for deletion in next backup cycle
deleteFromAnalytics(userId),
deleteFromThirdPartyServices(userId),
revokeAPIKeys(userId),
anonymizeHistoricalRecords(userId)
]);
// Confirm deletion
await sendDeletionConfirmation(email);
await logDeletionRequest(userId, 'completed');
return { status: 'deleted', timestamp: new Date() };
}
Exceptions (when deletion can be refused):
Export Handler:
async function handlePortabilityRequest(userId, format = 'json') {
const userData = await collectUserData(userId);
// Structure in machine-readable format
const portableData = {
exportDate: new Date().toISOString(),
userId: userId,
data: {
profile: userData.profile,
content: userData.userGeneratedContent,
settings: userData.preferences,
history: userData.activityHistory
}
};
// Support multiple formats
if (format === 'csv') {
return convertToCSV(portableData);
} else if (format === 'xml') {
return convertToXML(portableData);
}
return portableData; // JSON by default
}
Requirements:
Objection Handler:
async function handleObjectionRequest(userId, processingType) {
switch (processingType) {
case 'direct_marketing':
// Must stop immediately
await disableMarketing(userId);
await updateConsent(userId, 'marketing', false);
break;
case 'legitimate_interest':
// Assess if we have compelling grounds
const assessment = await assessLegitimateInterest(userId);
if (!assessment.compelling) {
await stopProcessing(userId, processingType);
}
return assessment;
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
davila7/claude-code-templates
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
data-privacy-compliance reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: data-privacy-compliance is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for data-privacy-compliance matched our evaluation — installs cleanly and behaves as described in the markdown.
I recommend data-privacy-compliance for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
data-privacy-compliance fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
data-privacy-compliance has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in data-privacy-compliance — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: data-privacy-compliance is focused, and the summary matches what you get after install.
I recommend data-privacy-compliance for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in data-privacy-compliance — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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