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From data-privacy
Implements anonymization and pseudonymization techniques for PII protection in datasets or tables, producing a formatted report of techniques applied and processed fields with examples.
How this command is triggered — by the user, by Claude, or both
Slash command
/data-privacy:anonymizeThe summary Claude sees in its command listing — used to decide when to auto-load this command
Implement data anonymization and pseudonymization for PII protection. ## Steps 1. Identify data that needs anonymization: 2. Choose the anonymization technique: 3. Implement anonymization: 4. Build the anonymization pipeline: 5. Verify anonymization: 6. Automate the pipeline for recurring use. ## Format ## Rules - Never use production data in development without anonymization. - Pseudonymized data must not be reversible without the key. - Maintain referential integrity across related tables.
Implement data anonymization and pseudonymization for PII protection.
Anonymization: <dataset or table>
Technique: <masking|pseudonymization|generalization>
Fields Processed:
- <field>: <technique applied> (<example>)
npx claudepluginhub rohitg00/awesome-claude-code-toolkit --plugin data-privacy/dpiaGuides GDPR Data Protection Impact Assessment (DPIA) execution for a processing activity name, optionally at screening, assessment, or review stage.
/classify-dataConduct data classification and define protection requirements for each classification level.
/check-piiScans text or file for PII (emails, SSNs, credit cards, phones, API keys, tokens), reports detected types, and shows redacted version with labels like [EMAIL], [SSN].
/pipelineCreates or repairs Redpanda Connect pipeline configurations interactively with guidance and validation, using required context and optional existing file.
/partitioningDesigns and implements PostgreSQL table partitioning for massive datasets, including schema design, automated maintenance, query optimization, and data retention policies.