--- name: lokalise-data-handling-ba172e7db5a8 description: | Implement Lokalise translation data handling, PII management, and compliance patterns. Use when handling sensitive translation data, implementing data redaction, or ensuring compliance with privacy regulations for Lokalise integrations. Trigger with phrases like "lokalise data", "lokalise PII", "lokalise GDPR", "lokalise data retention", "lokalise privacy", "lokalise compliance". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore --- # Lokalise Data Handling ## Overview Handle translation data correctly with privacy, compliance, and data governance best practices. ## Prerequisites - Understanding of GDPR/CCPA requirements - Lokalise SDK installed - Database for audit logging - Data classification policies ## Data Classification | Category | Examples | Handling | |----------|----------|----------| | Translation Keys | `welcome.message`, `error.network` | Standard | | UI Text | "Welcome!", "Submit" | Standard | | Dynamic Content | `Hello, {name}` | Review for PII | | User-Generated | Comments, descriptions | May contain PII | | API Tokens | `abc123...` | Never log | | Screenshots | Context images | May contain PII | ## Instructions ### Step 1: Translation Content Scanning ```typescript // Scan translations for potential PII before upload const PII_PATTERNS = [ { type: "email", regex: /[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}/g }, { type: "phone", regex: /\b\d{3}[-.]?\d{3}[-.]?\d{4}\b/g }, { type: "ssn", regex: /\b\d{3}-\d{2}-\d{4}\b/g }, { type: "credit_card", regex: /\b\d{4}[- ]?\d{4}[- ]?\d{4}[- ]?\d{4}\b/g }, { type: "ip_address", regex: /\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b/g }, ]; interface PIIFinding { type: string; match: string; key: string; language: string; } function scanTranslationsForPII( translations: Record, language: string ): PIIFinding[] { const findings: PIIFinding[] = []; for (const [key, value] of Object.entries(translations)) { for (const pattern of PII_PATTERNS) { const matches = value.matchAll(pattern.regex); for (const match of matches) { findings.push({ type: pattern.type, match: match[0], key, language, }); } } } return findings; } // Pre-upload validation async function validateBeforeUpload(filePath: string): Promise<{ valid: boolean; findings: PIIFinding[]; }> { const content = JSON.parse(fs.readFileSync(filePath, "utf8")); const locale = path.basename(filePath, ".json"); const findings = scanTranslationsForPII(content, locale); if (findings.length > 0) { console.warn("PII detected in translations:"); findings.forEach(f => { console.warn(` ${f.type} in ${f.key} (${f.language}): ${f.match}`); }); } return { valid: findings.length === 0, findings, }; } ``` ### Step 2: Safe Logging Practices ```typescript // Never log API tokens or sensitive translation content function safeLokaliseLog( operation: string, data: Record ): void { const sanitized = { ...data }; // Remove sensitive fields delete sanitized.apiToken; delete sanitized.apiKey; delete sanitized.webhookSecret; // Truncate large translation content if (sanitized.translation && typeof sanitized.translation === "string") { sanitized.translation = sanitized.translation.length > 100 ? `${sanitized.translation.slice(0, 100)}...` : sanitized.translation; } // Mask key IDs in production if (process.env.NODE_ENV === "production" && sanitized.keyId) { sanitized.keyId = "***"; } console.log(`[Lokalise] ${operation}:`, sanitized); } // Usage safeLokaliseLog("translation.update", { projectId: "123456.abc", keyId: 789, language: "es", translation: "Updated translation text here...", }); ``` ### Step 3: Data Retention Management ```typescript interface RetentionPolicy { dataType: string; retentionDays: number; reason: string; } const RETENTION_POLICIES: RetentionPolicy[] = [ { dataType: "api_logs", retentionDays: 30, reason: "Debugging" }, { dataType: "error_logs", retentionDays: 90, reason: "Root cause analysis" }, { dataType: "audit_logs", retentionDays: 2555, reason: "Compliance (7 years)" }, { dataType: "webhook_payloads", retentionDays: 7, reason: "Retry/debugging" }, { dataType: "translation_cache", retentionDays: 1, reason: "Performance" }, ]; async function enforceRetention(dataType: string): Promise { const policy = RETENTION_POLICIES.find(p => p.dataType === dataType); if (!policy) { throw new Error(`No retention policy for ${dataType}`); } const cutoff = new Date(); cutoff.setDate(cutoff.getDate() - policy.retentionDays); const deleted = await db.lokaliseData.deleteMany({ dataType, createdAt: { $lt: cutoff }, }); console.log(`Retention: Deleted ${deleted.count} ${dataType} records older than ${policy.retentionDays} days`); return deleted.count; } // Schedule daily cleanup // cron.schedule('0 3 * * *', () => { // RETENTION_POLICIES.forEach(p => enforceRetention(p.dataType)); // }); ``` ### Step 4: Audit Logging ```typescript interface AuditEntry { timestamp: Date; userId: string; action: string; resource: string; projectId: string; details?: Record; ipAddress?: string; } async function auditLokaliseAction(entry: Omit): Promise { const audit: AuditEntry = { ...entry, timestamp: new Date(), }; // Store in audit log (separate from regular logs) await db.auditLog.insert(audit); // Log for real-time monitoring console.log("[AUDIT]", JSON.stringify(audit)); } // Usage await auditLokaliseAction({ userId: currentUser.id, action: "translation.update", resource: `key:${keyId}`, projectId: "123456.abc", details: { language: "es", previousValue: "[REDACTED]", newValue: "[REDACTED]", }, ipAddress: request.ip, }); ``` ### Step 5: Data Export for Compliance ```typescript // GDPR Data Subject Access Request (DSAR) async function exportUserTranslationActivity(userId: string): Promise<{ user: { id: string; email: string }; activity: AuditEntry[]; exportedAt: string; }> { // Get all Lokalise-related activity for user const activity = await db.auditLog.find({ userId, resource: { $regex: /^lokalise/ }, }); return { user: { id: userId, email: "[from user database]" }, activity: activity.map(a => ({ ...a, // Redact sensitive details details: { action: a.details?.action, timestamp: a.timestamp }, })), exportedAt: new Date().toISOString(), }; } // Right to deletion async function deleteUserTranslationData(userId: string): Promise<{ deletedRecords: number; auditLogRetained: boolean; }> { // Delete user's cached data const deleted = await db.translationCache.deleteMany({ userId }); // Note: Audit logs may need to be retained for compliance // Instead of deleting, anonymize await db.auditLog.updateMany( { userId }, { $set: { userId: "DELETED_USER", userEmail: "REDACTED" } } ); // Log the deletion itself await auditLokaliseAction({ userId: "system", action: "gdpr.deletion", resource: `user:${userId}`, projectId: "all", details: { reason: "GDPR right to deletion" }, }); return { deletedRecords: deleted.count, auditLogRetained: true, }; } ``` ## Output - PII scanning for translations - Safe logging practices - Data retention enforcement - Audit trail for compliance ## Error Handling | Issue | Cause | Solution | |-------|-------|----------| | PII in translations | User-submitted content | Scan before upload | | Token in logs | Improper logging | Use safe log wrapper | | Audit gaps | Missing logging | Add audit calls | | Retention violation | No cleanup | Schedule retention jobs | ## Examples ### Pre-commit PII Check ```bash #!/bin/bash # .husky/pre-commit # Check for PII in translation files node scripts/scan-translations-pii.js if [ $? -ne 0 ]; then echo "PII detected in translations. Please review and remove." exit 1 fi ``` ### Compliance Checklist ```markdown ## Translation Data Compliance Checklist ### Data Collection - [ ] Only necessary data collected - [ ] User consent for personalized content - [ ] Purpose documented ### Storage - [ ] Translations stored securely - [ ] API tokens in secret manager - [ ] Cache encrypted at rest ### Retention - [ ] Retention policies defined - [ ] Automatic cleanup scheduled - [ ] Audit logs retained per regulations ### Access - [ ] Role-based access to projects - [ ] Access logged and auditable - [ ] Regular access reviews ### User Rights - [ ] Data export capability - [ ] Deletion process documented - [ ] Anonymization procedures ``` ### Quick PII Scan ```typescript const result = await validateBeforeUpload("./locales/en.json"); if (!result.valid) { console.error("Cannot upload: PII detected"); result.findings.forEach(f => console.error(` ${f.type}: ${f.key}`)); process.exit(1); } ``` ## Resources - [GDPR Developer Guide](https://gdpr.eu/developers/) - [CCPA Compliance](https://oag.ca.gov/privacy/ccpa) - [Lokalise Privacy](https://lokalise.com/privacy-policy) ## Next Steps For enterprise access control, see `lokalise-enterprise-rbac`. --- Source attribution: Dicklesworthstone Original project: https://github.com/Dicklesworthstone/pi_agent_rust/blob/f28fc46ee0db8e710d95b8b55592cd38d60f2b26/tests/ext_conformance/artifacts/plugins-community/plugins/saas-packs/lokalise-pack/skills/lokalise-data-handling/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License (with OpenAI/Anthropic Rider) Copyright (c) 2026 Jeffrey Emanuel Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: ADDITIONAL RIDER / RESTRICTION (OpenAI / Anthropic): This rider is part of the "conditions" of this License. In the event of any conflict between this rider and any other portion of this License, this rider controls. "Restricted Parties" means OpenAI, L.L.C.; Anthropic, PBC; any of their respective Affiliates; and any person or entity acting directly or indirectly on behalf of, for the benefit of, or under the direction of any of the foregoing (including any officer, director, employee, contractor, agent, consultant, service provider, or representative). Notwithstanding any other provision of this License, no rights are granted to any Restricted Party. Any purported license, sublicense, assignment, transfer, or other permission to any Restricted Party is null and void absent the express prior written permission of Jeffrey Emanuel. You may not provide, disclose, distribute, sublicense, sell, lease, lend, host, make available, or otherwise permit access to the Software or any derivative work of the Software (as defined in applicable copyright law) (collectively, "Derivative Works") to or for any Restricted Party. For purposes of this rider, "use" includes, without limitation: copying, modifying, merging, publishing, distributing, sublicensing, selling, transferring, making available, hosting, deploying, executing, benchmarking, testing, analyzing, indexing, or incorporating the Software or any Derivative Works into any dataset, training corpus, evaluation harness, or pipeline for machine learning or other automated systems. This rider applies to the Software and all Derivative Works. As a condition of use, you agree that this rider is a precondition to exercising any rights under this License, and you agree that any distribution of the Software or any Derivative Works must include this rider provision unmodified. Any breach of this rider automatically and immediately terminates the permissions granted by this License. Upon termination, you must immediately cease all use and distribution of the Software and any Derivative Works and destroy all copies under your control. You agree that a breach of this rider would cause irreparable harm and that Jeffrey Emanuel may seek injunctive or other equitable relief to enforce this rider, in addition to any other remedies available at law. To the maximum extent permitted by applicable law, the prevailing party in any action to enforce this rider shall be entitled to recover reasonable attorneys' fees and costs. For purposes of this rider, "Affiliate" means any entity that directly or indirectly controls, is controlled by, or is under common control with the specified party. "Control" means ownership of more than 50% of the voting securities or other ownership interest, or the power to direct management or policies by contract or otherwise. The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: Dicklesworthstone Original project: https://github.com/Dicklesworthstone/pi_agent_rust/blob/f28fc46ee0db8e710d95b8b55592cd38d60f2b26/tests/ext_conformance/artifacts/plugins-community/plugins/saas-packs/lokalise-pack/skills/lokalise-data-handling/SKILL.md Attribution basis: Source repository record Fields of work: Marketing Roles: Content Marketer, Growth Marketer, Marketing Analyst, Product Marketer, SEO Specialist Specialties: API Tools: Lokalise Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 4bf9233136c1d05af564c8cdb53ef9a2e1bd94359746e1ab3728477f59cbb6e5