# Gdpr Data Handling

> Implement GDPR-compliant data handling with consent management, data subject rights, and privacy by design. Use when building systems that process EU personal data, implementing privacy controls, o... Use when this capability is needed.

- Skill: `tomevault-io/gdpr-data-handling-2` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/gdpr-data-handling-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/gdpr-data-handling-2/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/gdpr-data-handling-2

---


# GDPR Data Handling

Practical implementation guide for GDPR-compliant data processing, consent management, and privacy controls.

## Use this skill when

- 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

## Do not use this skill when

- The task is unrelated to gdpr data handling
- You need a different domain or tool outside this scope

## Instructions

- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open `resources/implementation-playbook.md`.

## Resources

- `resources/implementation-playbook.md` for detailed patterns and examples.

---

<!-- AGI-INTEGRATION-START -->

## AGI Framework Integration

> **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)**
> Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills)

### Memory-First Protocol

Cache data schemas, transformation rules, and query patterns. BM25 excels at finding specific column names, table references, and SQL patterns.

```bash
# Check for prior data engineering context before starting
python3 execution/memory_manager.py auto --query "data processing patterns and pipeline configurations for Gdpr Data Handling"
```

### Storing Results

After completing work, store data engineering decisions for future sessions:

```bash
python3 execution/memory_manager.py store \
  --content "Data pipeline: ETL from PostgreSQL to Qdrant, 50K records/batch, incremental sync via updated_at" \
  --type technical --project <project> \
  --tags gdpr-data-handling data
```

### Multi-Agent Collaboration

Share data schema changes with backend and frontend agents so they update their models accordingly.

```bash
python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Data pipeline implemented — ETL processing with validation, deduplication, and error recovery" \
  --project <project>
```

<!-- AGI-INTEGRATION-END -->

---
> Converted and distributed by [TomeVault](https://tomevault.io/claim/techwavedev) — claim your Tome and manage your conversions.
<!-- tomevault:4.0:skill_md:2026-04-13 -->