lawve-ai/dpia-sentinel-oliver-schmidt-prietz
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npx skills add https://github.com/lawve-ai/awesome-legal-skills --skill dpia-sentinel-oliver-schmidt-prietz
> Important: This skill provides structured GDPR Article 35 guidance based on EDPB Guidelines and national SA requirements. It is not legal advice. Involve your DPO (Art. 35(2)) and qualified counsel for final decisions.
Determine what the user needs and load references accordingly:
| User Need | Load These References | Action |
|-----------|----------------------|--------|
| "Do I need a DPIA?" / threshold question | references/edpb-criteria.md + relevant jurisdiction file(s) | Run threshold assessment |
| Full DPIA | edpb-criteria.md + jurisdiction(s) + references/risk-catalog.md + scoring.md | Walk through assessment phases |
| Document generation (.docx) — custom format | references/dpia-custom-population.md + references/templates.md + docx skill | Populate custom template .docx (unpack → fill tables → repack) |
| Document generation (.docx) — EDPB 2026 format | references/edpb-2026-population.md + references/edpb-2026-template.md + docx skill | Populate official EDPB template .docx (unpack → fill tables → repack) |
| Specific legal question | Load relevant reference only | Answer directly |
Jurisdiction selection: Ask two questions: (1) Where is the controller's main establishment? (2) Where are the data subjects located? Load all jurisdiction files that are relevant — this may be multiple files for multi-jurisdictional processing. See references/edpb-criteria.md → "Multi-Jurisdictional DPIA Analysis" for the full decision framework.
Available jurisdiction files:
references/jurisdictions/de-dsk.md — Germanyreferences/jurisdictions/fr-cnil.md — Francereferences/jurisdictions/ie-dpc.md — Irelandreferences/jurisdictions/be-apd.md — Belgiumreferences/jurisdictions/nl-ap.md — Netherlandsreferences/jurisdictions/it-garante.md — Italyreferences/jurisdictions/pl-uodo.md — Polandreferences/jurisdictions/whitelists.md — France, Czech Republic, Spain, AustriaFor jurisdictions not covered by a dedicated file, rely on the EDPB nine-criteria analysis in references/edpb-criteria.md and note that the user should check their national SA's Art. 35(4) list directly.
Threshold → Description → Asset Inventory → Necessity → Proportionality → Inherent Risks (Track A+B) → Mitigations → Residual Risk → Art. 36 Check → Documentation
This is the logical sequence, not a rigid script. Adapt to the user: if they provide rich context upfront, skip intake questions. If they're experienced, move faster. If they're new to DPIAs, explain more.
Asset Inventory (per EDPB Template 2026, Section 1.3): Collect risk-relevant assets — hardware, software, APIs/models, personnel, sites/premises, organisational assets. Group by logical module or technical layer. Include only assets whose compromise would plausibly impact data subjects' rights and freedoms.
Necessity and Proportionality are separate upstream gates (EDPB Template 2026, Section 3). Necessity: is the processing effective and least intrusive? Proportionality: do the benefits justify the impacts? These must be assessed *before* the risk mitigation phase.
Two risk tracks (per EDPB Template 2026): Track A identifies inherent-by-design risks (from processing working as intended). Track B identifies operational risks (from accidental/unlawful/abnormal events). Both are scored using the same L×S + modulating factors methodology in references/scoring.md.
The assessment is iterative: if mitigations in later stages change the processing design, revisit earlier analysis and flag this to the user.
These are areas where Claude's training knowledge may be imprecise. Always apply these rules:
references/edpb-criteria.md → "Multi-Jurisdictional DPIA Analysis" for details.10. Pseudonymization as risk reducer (EDPB Guidelines 01/2025 on Pseudonymisation, adopted 17 January 2025): Effective pseudonymization with technically separated additional information can meaningfully reduce likelihood scores in risk assessment. But it must be genuine — if re-identification is trivial, it doesn't reduce risk.
11. Risk assessment is from the data subject's perspective. A DPIA assesses risks to rights and freedoms of natural persons (Recital 75), not corporate/business risks. Identity theft risk to the individual, not reputational risk to the company.
12. AI Act FRIA is distinct from DPIA. For high-risk AI systems under the AI Act, a Fundamental Rights Impact Assessment (FRIA) may also be required. DPIA (data protection risks) and FRIA (broader fundamental rights) are complementary — one does not replace the other.
13. EDPB DPIA Template (v1.0, March 2026) provides a harmonised EU-wide DPIA structure but does not mandate a specific risk scoring methodology. Controllers may use any established methodology (CNIL PIA, DSK SDM, etc.); the template records the minimum required information in a standardised format. National SA requirements and methodologies remain valid complements. Note: the template was adopted for public consultation — check for final version updates.
Threshold result: Present a clear verdict (DPIA Required / Recommended / Not Required) with the reasoning showing Art. 35(3) check, criteria analysis, and national list check.
Risk register: Table with Risk ID, Track (A/B), Description, Rights Category, Likelihood (1-5), Severity (1-5), Score, Modulating Factors, Adjusted Level. Use the scoring methodology in references/scoring.md.
Residual risk overview: Summary showing total risks by level before and after additional mitigation, plus overall verdict (APPROVED / CONDITIONALLY APPROVED / CONSULT SA / REJECTED).
Documents: Both formats use template population (unpack → fill → repack) for consistent styling. Read the docx skill first, then the relevant population guide:
references/edpb-2026-template-v1.docx using references/edpb-2026-population.md. Official format recognized by all EU SAs.references/dpia-custom-template-v1.docx using references/dpia-custom-population.md. Includes threshold analysis, jurisdictional blacklist detail, risk heat maps, and annexes.> If the .docx template files are not present (some hosts, including lawve.ai, store text files only): build the Word document from scratch with the docx skill following the matching population guide — the population guides above fully specify every section, table, and field. The pre-styled .docx templates are available in the GitHub repo linked at the top of this skill if you want the exact corporate styling.
Ask the user which format they prefer.
This skill works standalone, but pairs well with my other EU data-protection skills — install any on its own or combine them:
Take lawve-ai/dpia-sentinel-oliver-schmidt-prietz from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.