gdpr-dsgvo-expert
GDPR and German DSGVO compliance automation. Scans codebases for privacy risks, generates DPIA documentation, tracks data subject rights requests with Art. 12(3) one-month deadlines. Use when running GDPR compliance assessments, privacy audits, data protection planning, DPIA generation, or data subject rights (DSAR) management (e.g., 'check this service for GDPR risks', 'track an access request deadline'). Final compliance determinations route to the DPO or legal counsel.
- License 许可
- MIT
- 最近更新
- 2026-07-04
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01 前言 Front Matter
- name
- gdpr-dsgvo-expert
- description
- GDPR and German DSGVO compliance automation. Scans codebases for privacy risks, generates DPIA documentation, tracks data subject rights requests with Art. 12(3) one-month deadlines. Use when running GDPR compliance assessments, privacy audits, data protection planning, DPIA generation, or data subject rights (DSAR) management (e.g., 'check this service for GDPR risks', 'track an access request deadline'). Final compliance determinations route to the DPO or legal counsel.
02 资源文件 7
- 参考文档references/dpia_methodology.md10.7 KB
- 参考文档references/gdpr_audit_playbook.md10.4 KB
- 参考文档references/gdpr_compliance_guide.md8.9 KB
- 参考文档references/german_bdsg_requirements.md8.7 KB
- 脚本scripts/data_subject_rights_tracker.py19.8 KB
- 脚本scripts/dpia_generator.py20.2 KB
- 脚本scripts/gdpr_compliance_checker.py15.1 KB
03 SKILL.md 正文
GDPR/DSGVO Expert
Tools and guidance for EU General Data Protection Regulation (GDPR) and German Bundesdatenschutzgesetz (BDSG) compliance.
Table of Contents
Tools
GDPR Compliance Checker
Scans codebases for potential GDPR compliance issues including personal data patterns and risky code practices.
# Scan a project directory
python scripts/gdpr_compliance_checker.py /path/to/project
# JSON output for CI/CD integration
python scripts/gdpr_compliance_checker.py . --json --output report.json
Detects:
- Personal data patterns (email, phone, IP addresses)
- Special category data (health, biometric, religion)
- Financial data (credit cards, IBAN)
- Risky code patterns:
- Logging personal data
- Missing consent mechanisms
- Indefinite data retention
- Unencrypted sensitive data
- Disabled deletion functionality
Output:
- Compliance score (0-100)
- Risk categorization (critical, high, medium)
- Prioritized recommendations with GDPR article references
DPIA Generator
Generates Data Protection Impact Assessment documentation following Art. 35 requirements.
# Get input template
python scripts/dpia_generator.py --template > input.json
# Generate DPIA report
python scripts/dpia_generator.py --input input.json --output dpia_report.md
Features:
- Automatic DPIA threshold assessment
- Risk identification based on processing characteristics
- Legal basis requirements documentation
- Mitigation recommendations
- Markdown report generation
DPIA Triggers Assessed:
- Systematic monitoring (Art. 35(3)(c))
- Large-scale special category data (Art. 35(3)(b))
- Automated decision-making (Art. 35(3)(a))
- EDPB-endorsed high-risk criteria (WP248 rev.01)
Data Subject Rights Tracker
Manages data subject rights requests under GDPR Articles 15-22.
# Add new request
python scripts/data_subject_rights_tracker.py add \
--type access --subject "John Doe" --email "john@example.com"
# List all requests
python scripts/data_subject_rights_tracker.py list
# Update status
python scripts/data_subject_rights_tracker.py status --id DSR-202601-0001 --update verified
# Generate compliance report
python scripts/data_subject_rights_tracker.py report --output compliance.json
# Generate response template
python scripts/data_subject_rights_tracker.py template --id DSR-202601-0001
Supported Rights:
| Right | Article | Deadline |
|---|---|---|
| Access | Art. 15 | One month (Art. 12(3)) |
| Rectification | Art. 16 | One month (Art. 12(3)) |
| Erasure | Art. 17 | One month (Art. 12(3)) |
| Restriction | Art. 18 | One month (Art. 12(3)) |
| Portability | Art. 20 | One month (Art. 12(3)) |
| Objection | Art. 21 | One month (Art. 12(3)) |
| Automated decisions | Art. 22 | One month (Art. 12(3)) |
Features:
- Deadline tracking with overdue alerts
- Identity verification workflow
- Response template generation
- Compliance reporting
Reference Guides
GDPR Compliance Guide
references/gdpr_compliance_guide.md
Comprehensive implementation guidance covering:
- Legal bases for processing (Art. 6)
- Special category requirements (Art. 9)
- Data subject rights implementation
- Accountability requirements (Art. 30)
- International transfers (Chapter V)
- Breach notification (Art. 33-34)
German BDSG Requirements
references/german_bdsg_requirements.md
German-specific requirements including:
- DPO appointment threshold (§ 38 BDSG - 20+ employees)
- Employment data processing (§ 26 BDSG)
- Video surveillance rules (§ 4 BDSG)
- Credit scoring requirements (§ 31 BDSG)
- State data protection laws (Landesdatenschutzgesetze)
- Works council co-determination rights
DPIA Methodology
references/dpia_methodology.md
Step-by-step DPIA process:
- Threshold assessment criteria
- EDPB-endorsed high-risk indicators (WP248 rev.01)
- Risk assessment methodology
- Mitigation measure categories
- DPO and supervisory authority consultation
- Templates and checklists
Workflows
Workflow 1: New Processing Activity Assessment
Step 1: Run compliance checker on codebase
→ python scripts/gdpr_compliance_checker.py /path/to/code
Step 2: Review findings and compliance score
→ Address critical and high issues
Step 3: Determine if DPIA required
→ Check references/dpia_methodology.md threshold criteria
Step 4: If DPIA required, generate assessment
→ python scripts/dpia_generator.py --template > input.json
→ Fill in processing details
→ python scripts/dpia_generator.py --input input.json --output dpia.md
Step 5: Document in records of processing activities
Workflow 2: Data Subject Request Handling
Step 1: Log request in tracker
→ python scripts/data_subject_rights_tracker.py add --type [type] ...
Step 2: Verify identity (proportionate measures)
→ python scripts/data_subject_rights_tracker.py status --id [ID] --update verified
Step 3: Gather data from systems
→ python scripts/data_subject_rights_tracker.py status --id [ID] --update in_progress
Step 4: Generate response
→ python scripts/data_subject_rights_tracker.py template --id [ID]
Step 5: Send response and complete
→ python scripts/data_subject_rights_tracker.py status --id [ID] --update completed
Step 6: Monitor compliance
→ python scripts/data_subject_rights_tracker.py report
Workflow 3: German BDSG Compliance Check
Step 1: Determine if DPO required
→ 20+ employees processing personal data automatically
→ OR processing requires DPIA
→ OR business involves data transfer/market research
Step 2: If employees involved, review § 26 BDSG
→ Document legal basis for employee data
→ Check works council requirements
Step 3: If video surveillance, comply with § 4 BDSG
→ Install signage
→ Document necessity
→ Limit retention
Step 4: Register DPO with supervisory authority
→ See references/german_bdsg_requirements.md for authority list
Key GDPR Concepts
Legal Bases (Art. 6)
- Consent: Marketing, newsletters, analytics (must be freely given, specific, informed)
- Contract: Order fulfillment, service delivery
- Legal obligation: Tax records, employment law
- Legitimate interests: Fraud prevention, security (requires balancing test)
Special Category Data (Art. 9)
Requires explicit consent or Art. 9(2) exception:
- Health data
- Biometric data
- Racial/ethnic origin
- Political opinions
- Religious beliefs
- Trade union membership
- Genetic data
- Sexual orientation
Data Subject Rights
All rights must be fulfilled within one month of receipt (Art. 12(3)). The deadline runs by calendar month, not 30 days, and may be extended by two further months for complex or numerous requests — the data subject must be informed of the extension (with reasons) within the first month:
- Access: Provide copy of data and processing information
- Rectification: Correct inaccurate data
- Erasure: Delete data (with exceptions for legal obligations)
- Restriction: Limit processing while issues are resolved
- Portability: Provide data in machine-readable format
- Object: Stop processing based on legitimate interests
German BDSG Additions
| Topic | BDSG Section | Key Requirement |
|---|---|---|
| DPO threshold | § 38 | 20+ employees = mandatory DPO |
| Employment | § 26 | Detailed employee data rules |
| Video | § 4 | Signage and proportionality |
| Scoring | § 31 | Explainable algorithms |
04 同仓库更多 Skills
syllabus
Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Use when the user uploads a syllabus, course outline, or curriculum document and wants supplementary readings (e.g., 'create a reading list from this syllabus', 'find recent papers for my course') — even casual mentions with a syllabus attached should trigger this skill.
research
Default entry point for any research request — a hybrid router that classifies the question deterministically and either delegates to a specialist research skill (pulse for trends/sentiment, grants for NIH funding, litreview for academic literature, syllabus for course reading, patent for prior-art + IP landscape, dossier for entity research) or runs its own plan-decompose-multi-source-search-synthesize-cite fallback workflow when no specialist matches. Always surfaces the routing decision so users can override. Use when the user makes any research request that doesn't obviously match a more-specific specialist skill (e.g., "research [topic]", "look into [topic]", "what do we know about [topic]", "investigate [topic]", "find me information on [topic]", "do some research on [topic]", "I need to understand [topic]"). Output is a markdown briefing (default) or .docx document (on request) with full citations and an audit log.
pulse
Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Use when the user requests multi-source recency intelligence on a topic (e.g., 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]'), and for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.
patent
Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search / freedom-to-operate / competitive landscape / acquisition diligence / litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Use when the user asks for patent searching or analysis (e.g., 'prior art search for [invention]', 'freedom to operate analysis for [product]'). Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.
notebooklm
Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio/Video Overviews, Mind Maps, Reports incl. Briefing Doc/Study Guide/FAQ, Flashcards, Quiz, slide decks, infographics — discover the exact set from the live Studio panel; the UI evolves fast), and creating new notebooks. Requires browser automation environment — fails gracefully when unavailable.
litreview
Academic literature orientation skill that searches papers via free keyless APIs (PubMed E-utilities + OpenAlex) by default — with the Consensus MCP as an optional enhancement lane when connected — builds a strategic search plan using PICO (default) or SPIDER / Decomposition / hybrid as fallbacks, and synthesizes findings into a formatted Word (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5/10/20 queries) controls coverage vs. speed. Output is a 'launching pad' — an orientation guide that lets a researcher dive in confidently, not a finished review. Use when the user starts literature-oriented research (e.g., 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'). Do NOT use for single one-off paper searches wanting a quick list — that's a plain PubMed/OpenAlex (or Consensus) query.