clay-data-handling
Implements GDPR/CCPA-compliant data handling and retention policies for Clay enrichment workflows.
Install
mkdir -p .claude/skills/clay-data-handling && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4687" && unzip -o skill.zip -d .claude/skills/clay-data-handling && rm skill.zipInstalls to .claude/skills/clay-data-handling
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Implement GDPR/CCPA-compliant data handling for Clay enrichment pipelines.Key capabilities
- →Classify enriched data by sensitivity levels.
- →Validate input data before enrichment.
- →Deduplicate leads to prevent credit waste.
- →Add retention metadata to enriched records.
- →Anonymize data for analytics exports.
- →Handle data subject deletion requests.
How it works
The skill provides code patterns to classify data sensitivity, validate and deduplicate input, add retention metadata, anonymize data for export, and process data subject deletion requests.
Inputs & outputs
When to use clay-data-handling
- →Implementing PII redaction
- →Configuring data retention policies
- →Ensuring GDPR compliance
- →Classifying sensitive data fields
About this skill
Clay Data Handling
Overview
Manage lead data through Clay enrichment pipelines in compliance with GDPR, CCPA, and data privacy best practices. Clay enriches records with PII (emails, phone numbers, LinkedIn profiles, job titles), requiring careful handling of consent, retention, and export controls.
Prerequisites
- Clay account with enriched tables
- Understanding of GDPR/CCPA requirements for B2B data
- Data retention policy defined by your legal team
- CRM or database for enriched data storage
Instructions
Step 1: Classify Enriched Data by Sensitivity
// src/clay/data-classification.ts
enum DataSensitivity {
PUBLIC = 'public', // Company name, industry, employee count
BUSINESS = 'business', // Work email, job title, LinkedIn URL
PERSONAL = 'personal', // Phone number, personal email
RESTRICTED = 'restricted' // Home address, personal phone
}
const FIELD_CLASSIFICATION: Record<string, DataSensitivity> = {
company_name: DataSensitivity.PUBLIC,
industry: DataSensitivity.PUBLIC,
employee_count: DataSensitivity.PUBLIC,
domain: DataSensitivity.PUBLIC,
work_email: DataSensitivity.BUSINESS,
job_title: DataSensitivity.BUSINESS,
linkedin_url: DataSensitivity.BUSINESS,
first_name: DataSensitivity.BUSINESS,
last_name: DataSensitivity.BUSINESS,
phone_number: DataSensitivity.PERSONAL,
personal_email: DataSensitivity.RESTRICTED,
home_address: DataSensitivity.RESTRICTED,
};
function classifyRow(row: Record<string, unknown>): Record<DataSensitivity, string[]> {
const classified: Record<DataSensitivity, string[]> = {
public: [], business: [], personal: [], restricted: [],
};
for (const [field, value] of Object.entries(row)) {
if (value == null) continue;
const sensitivity = FIELD_CLASSIFICATION[field] || DataSensitivity.BUSINESS;
classified[sensitivity].push(field);
}
return classified;
}
Step 2: Validate Input Data Before Enrichment
// src/clay/data-validation.ts
import { z } from 'zod';
const ClayInputSchema = z.object({
domain: z.string().min(3).refine(d => d.includes('.'), 'Invalid domain'),
first_name: z.string().min(1).max(100),
last_name: z.string().min(1).max(100),
email: z.string().email().optional(),
source: z.string().optional(),
consent_basis: z.enum(['legitimate_interest', 'consent', 'contract']).optional(),
});
function validateForEnrichment(rows: unknown[]): {
valid: z.infer<typeof ClayInputSchema>[];
invalid: { row: unknown; errors: string[] }[];
} {
const valid: z.infer<typeof ClayInputSchema>[] = [];
const invalid: { row: unknown; errors: string[] }[] = [];
for (const row of rows) {
const result = ClayInputSchema.safeParse(row);
if (result.success) {
valid.push(result.data);
} else {
invalid.push({
row,
errors: result.error.issues.map(i => `${i.path.join('.')}: ${i.message}`),
});
}
}
return { valid, invalid };
}
Step 3: Deduplicate Before Enrichment
// src/clay/dedup.ts — prevent credit waste on duplicates
function deduplicateLeads(
rows: Record<string, unknown>[],
keyFields: string[] = ['domain', 'first_name', 'last_name'],
): { unique: Record<string, unknown>[]; duplicates: number } {
const seen = new Set<string>();
const unique: Record<string, unknown>[] = [];
let duplicates = 0;
for (const row of rows) {
const key = keyFields
.map(f => String(row[f] || '').toLowerCase().trim())
.join(':');
if (seen.has(key)) {
duplicates++;
continue;
}
seen.add(key);
unique.push(row);
}
return { unique, duplicates };
}
Step 4: Add Retention Metadata to Enriched Data
// src/clay/retention.ts
interface EnrichedRecordWithRetention {
// Original enriched data
[key: string]: unknown;
// Retention metadata
_enriched_at: string; // ISO timestamp
_retention_expires: string; // ISO timestamp
_enrichment_source: string; // 'clay'
_consent_basis: string; // Legal basis for processing
_data_subject_rights: string; // How to handle deletion requests
}
function addRetentionMetadata(
enrichedRow: Record<string, unknown>,
retentionDays: number = 365,
consentBasis: string = 'legitimate_interest',
): EnrichedRecordWithRetention {
const now = new Date();
const expires = new Date(now.getTime() + retentionDays * 24 * 60 * 60 * 1000);
return {
...enrichedRow,
_enriched_at: now.toISOString(),
_retention_expires: expires.toISOString(),
_enrichment_source: 'clay',
_consent_basis: consentBasis,
_data_subject_rights: 'Contact [email protected] for deletion/access requests',
};
}
Step 5: GDPR-Compliant Export
// src/clay/export.ts
/** Strip PII for analytics/reporting exports */
function anonymizeForAnalytics(row: Record<string, unknown>): Record<string, unknown> {
const anonymized = { ...row };
// Hash identifiers instead of including plaintext
if (anonymized.work_email) {
anonymized.email_hash = crypto.createHash('sha256')
.update(String(anonymized.work_email).toLowerCase())
.digest('hex');
delete anonymized.work_email;
}
// Remove all personal identifiers
delete anonymized.first_name;
delete anonymized.last_name;
delete anonymized.phone_number;
delete anonymized.linkedin_url;
delete anonymized.personal_email;
return anonymized;
}
/** Full export for CRM push (with consent tracking) */
function exportForCRM(row: Record<string, unknown>): Record<string, unknown> {
return {
...row,
processing_consent: row._consent_basis || 'legitimate_interest',
enrichment_date: row._enriched_at,
data_source: 'clay_enrichment',
};
}
Step 6: Data Subject Rights Implementation
// src/clay/data-rights.ts — handle GDPR deletion/access requests
async function handleDeletionRequest(email: string): Promise<{
tablesAffected: string[];
recordsDeleted: number;
}> {
// In Clay: manually delete rows containing this email
// In your database: automated deletion
console.log(`Processing deletion request for ${email}`);
// 1. Find all records
const records = await db.query('SELECT * FROM enriched_leads WHERE email = ?', [email]);
// 2. Delete from database
await db.query('DELETE FROM enriched_leads WHERE email = ?', [email]);
// 3. Log for compliance audit
await db.query('INSERT INTO deletion_log (email_hash, deleted_at, record_count) VALUES (?, ?, ?)', [
crypto.createHash('sha256').update(email).digest('hex'),
new Date().toISOString(),
records.length,
]);
// 4. Note: Clay table rows must be deleted manually in Clay UI
return {
tablesAffected: ['enriched_leads'],
recordsDeleted: records.length,
};
}
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| High duplicate rate | Same list imported twice | Run dedup before sending to Clay |
| Invalid emails in export | Bad source data | Validate with Zod before import |
| Expired data in CRM | No retention cleanup | Schedule weekly expiration check |
| Missing consent basis | No legal basis tracked | Add consent_basis to all records |
| GDPR deletion incomplete | Data in multiple systems | Track all systems in data map |
Resources
Next Steps
For access control, see clay-enterprise-rbac.
When not to use it
- →When no data retention policy is defined by a legal team.
- →When there is no CRM or database for enriched data storage.
Prerequisites
Limitations
- →High duplicate rates can occur if dedup is not run before sending to Clay.
- →GDPR deletion may be incomplete if data resides in multiple systems.
How it compares
This skill provides specific code patterns for GDPR/CCPA-compliant data handling in Clay enrichment pipelines, unlike general data privacy guidelines.
Compared to similar skills
clay-data-handling side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| clay-data-handling (this skill) | 1 | 27d | No flags | Intermediate |
| reverse-engineering-tools | 73 | 4mo | No flags | Advanced |
| game-hacking-techniques | 42 | 2mo | No flags | Advanced |
| solidity-security | 15 | 2mo | No flags | Intermediate |
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Example prompts that trigger this skill in your AI assistant.
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