Dpia Sentinel Oliver Schmidt Prietz logo

Dpia Sentinel Oliver Schmidt Prietz

Organization
lawve-ai
dpia-sentinel-oliver-schmidt-prietz

GDPR Data Protection Impact Assessment (DPIA) guidance under Article 35 GDPR, EDPB Guidelines WP 248 rev.01, EDPB Opinion 28/2024 (AI), and national SA blacklists/whitelists. Triggers: "DPIA", "DSFA", "Datenschutz-Folgenabschätzung", "impact assessment", "Art. 35", "do I need a DPIA", descriptions of new high-risk processing (profiling, AI, biometrics, large-scale monitoring, special category data), Art. 36 prior consultation questions, national blacklist/whitelist queries.

Overview

Publisherlawve-ai
Repositoryawesome-legal-skills
Skill namedpia-sentinel-oliver-schmidt-prietz
Stars
854
Forks
111
Bundled files
18
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 18 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by lawve-ai on GitHub. Read the source before you install it.

Installation

Install the Dpia Sentinel Oliver Schmidt Prietz AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/lawve-ai/awesome-legal-skills/tree/main/skills/dpia-sentinel-oliver-schmidt-prietz
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/lawve-ai/awesome-legal-skills.git /tmp/awesome-legal-skills
mkdir -p .claude/skills
cp -r /tmp/awesome-legal-skills/skills/dpia-sentinel-oliver-schmidt-prietz .claude/skills/dpia-sentinel-oliver-schmidt-prietz
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dpia Sentinel Oliver Schmidt Prietz in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dpia Sentinel Oliver Schmidt Prietz on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dpia Sentinel Oliver Schmidt Prietz is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

DPIA Sentinel

Disclaimer (show at session start, do not block)

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.

Routing

Determine what the user needs and load references accordingly:

User NeedLoad These ReferencesAction
"Do I need a DPIA?" / threshold questionreferences/edpb-criteria.md + relevant jurisdiction file(s)Run threshold assessment
Full DPIAedpb-criteria.md + jurisdiction(s) + references/risk-catalog.md + scoring.mdWalk through assessment phases
Document generation (.docx) — custom formatreferences/dpia-custom-population.md + references/templates.md + docx skillPopulate custom template .docx (unpack → fill tables → repack)
Document generation (.docx) — EDPB 2026 formatreferences/edpb-2026-population.md + references/edpb-2026-template.md + docx skillPopulate official EDPB template .docx (unpack → fill tables → repack)
Specific legal questionLoad relevant reference onlyAnswer 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 — Germany
  • references/jurisdictions/fr-cnil.md — France
  • references/jurisdictions/ie-dpc.md — Ireland
  • references/jurisdictions/be-apd.md — Belgium
  • references/jurisdictions/nl-ap.md — Netherlands
  • references/jurisdictions/it-garante.md — Italy
  • references/jurisdictions/pl-uodo.md — Poland
  • references/jurisdictions/whitelists.md — France, Czech Republic, Spain, Austria

For 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.

Assessment Flow

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.

Legal Precision Points

These are areas where Claude's training knowledge may be imprecise. Always apply these rules:

  1. Art. 35(3) triggers are absolute. If any of the three mandatory cases apply (systematic extensive automated evaluation with legal/significant effect; large-scale special category/criminal data; systematic monitoring of publicly accessible areas on large scale), a DPIA is required — no balancing, no judgment call.

  2. The two-criteria rule is a presumption, not a mandate. Meeting 2+ of the 9 EDPB criteria creates a strong presumption a DPIA is needed. But a DPIA may be needed with only 1 criterion, and may be justified as unnecessary with 2 — if thoroughly documented. See WP 248 rev.01, p. 11.

  3. Art. 9 is cumulative with Art. 6. Special category data always needs BOTH a legal basis under Art. 6 AND an exception under Art. 9(2). These are separate legal hurdles.

  4. "Large scale" has no fixed number. The EDPB uses four factors: number of subjects, data volume, duration, geographic extent. An individual doctor is not large scale; a regional hospital is. Never cite a specific numerical threshold.

  5. National blacklists are additive, not exhaustive. Processing not on a blacklist may still require a DPIA. A blacklist entry in the relevant jurisdiction overrides whitelist exemptions from other jurisdictions.

  6. Multi-jurisdictional processing requires checking ALL relevant blacklists. Art. 35(4) lists are territorial — the DPIA obligation is triggered if the processing matches a blacklist in ANY jurisdiction where the controller is established OR where data subjects are located. The one-stop-shop mechanism (Art. 56) governs enforcement jurisdiction, but it does NOT limit which Art. 35(4) lists apply to the DPIA obligation itself. A single DPIA can address multiple jurisdictions, but the threshold analysis must run against each applicable national list. See references/edpb-criteria.md → "Multi-Jurisdictional DPIA Analysis" for details.

  7. DPIA must happen before processing begins (Art. 35(1)). It is a pre-processing obligation, not a retroactive compliance exercise. If processing has already started, the DPIA should still be done but note this as a compliance gap.

  8. AI requires dual-phase analysis (EDPB Opinion 28/2024). Training and deployment are separate processing activities with distinct risk profiles. A deployer cannot simply rely on the model provider's DPIA.

  9. Art. 36 prior consultation is sequential to the DPIA, not part of it. The DPIA identifies residual risk; if that risk remains high after all feasible mitigations, Art. 36 requires consulting the SA before processing begins. The SA has 8 weeks (extendable by 6).

  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.

Output Formats

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:

  • EDPB 2026 format: Populate references/edpb-2026-template-v1.docx using references/edpb-2026-population.md. Official format recognized by all EU SAs.
  • Custom 12-section format: Populate 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.

Related GDPR skills

This skill works standalone, but pairs well with my other EU data-protection skills — install any on its own or combine them:

  • GDPR Breach Sentinel — Art. 33/34 breach response & notification
  • Privacy Notice Generator — Art. 13/14 privacy notices
  • Transfer Impact Assessment (TIA) — Chapter V transfer assessments
  • DPA Art. 28 — controller–processor agreements (AVV)
  • Legitimate Interest — Art. 6(1)(f) LIA / balancing test

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Dpia Sentinel Oliver Schmidt Prietz AI skill do?

GDPR Data Protection Impact Assessment (DPIA) guidance under Article 35 GDPR, EDPB Guidelines WP 248 rev.01, EDPB Opinion 28/2024 (AI), and national SA blacklists/whitelists. Triggers: "DPIA", "DSFA", "Datenschutz-Folgenabschätzung", "impact assessment", "Art. 35", "do I need a DPIA", descriptions of new high-risk processing (profiling, AI, biometrics, large-scale monitoring, special category data), Art. 36 prior consultation questions, national blacklist/whitelist queries.

Why use Dpia Sentinel Oliver Schmidt Prietz on TypingMind?

Because you install it once and use it with any model. Dpia Sentinel Oliver Schmidt Prietz is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dpia Sentinel Oliver Schmidt Prietz in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lawve-ai/awesome-legal-skills/tree/main/skills/dpia-sentinel-oliver-schmidt-prietz. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dpia Sentinel Oliver Schmidt Prietz?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dpia Sentinel Oliver Schmidt Prietz?

As many as you like. As long as a model supports skills, you can use Dpia Sentinel Oliver Schmidt Prietz with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dpia Sentinel Oliver Schmidt Prietz AI skill free?

It is published on GitHub by lawve-ai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇