Agent skill · Design & Presentation

eu-ai-act-high-risk-classifier-oliver-schmidt-prietz

Depth assessment of whether an AI system is high-risk under Art. 6 of the EU AI Act, grounded in the Commission's draft Art. 6(5) classification guidelines (general principles + Annex I + Annex III). Covers the Annex I product-safety route, all eight Annex III areas with worked examples, the Art. 6(3) exception and its profiling re-exception, and the Art. 25 quasi-provider trap. Outputs a structured decision block, a practitioner memo, and a JSON interchange artefact.

lawve-aigithub.com/lawve-aiGitHub ↗
claude-codeNOASSERTION
Install
npx skills add lawve-ai/awesome-legal-skills --skill eu-ai-act-high-risk-classifier-oliver-schmidt-prietz --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 20
SKILL.md size: 18 KB
Bundled scripts: none
Version: 2026-06-09
Declared author: Oliver Schmidt-Prietz
Path: skills/eu-ai-act-high-risk-classifier-oliver-schmidt-prietz/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 618
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

Review
written from the skill's own SKILL.md · Aug 5, 2026

What it does

Depth assessment of whether an AI system is high-risk under Art. 6 AI Act, grounded in the Commission's draft Art. 6(5) classification guidelines (general principles, Annex I, Annex III). Outputs a structured decision block, a practitioner memo, and a JSON interchange artefact.

How it works

Follows a five-step decision tree:

  • Step 1: Gate the AI system definition per Art. 3(1).
  • Step 2: Document provider-stated intended purpose and gather inputs.
  • Step 3: Art. 6(1) / Annex I branch: determine if the system is a product/safety component, apply safety-function or failure-based tests, assess third-party conformity (Modules) and determine Annex I Section A or B mapping.
  • Step 4: Art. 6(2) / Annex III branch: map to eight Annex III areas, check Art. 6(3) exception (a–d) and profiling re-exception, and apply Art. 6(4) documentation if needed.
  • Step 5: Art. 25 substantial-modification trap if applicable.

Outputs three artefacts unless subset requested: a Structured decision block, a Practitioner memo, and a JSON interchange artefact.

From the SKILL.md

# EU AI Act High-Risk Classification Depth assessment of whether an AI system is **high-risk** under **Art. 6 AI Act** (Regulation (EU) 2024/1689), grounded in the European Commission's draft Art. 6(5) classification guidelines (general principles, Annex I, Annex III) published for stakeholder consultation in 2026. ## Disclaimer (show at session start, do not block) > **Important:** This skill provides structured high-risk classification guidance based on the EU AI Act (Regulation (EU) 2024/1689) and the Commission's draft Art. 6(5) classification guidelines (general principles, Annex I, Annex III) issued for stakeholder consultation. The Commission guidelines are non-binding; authoritative interpretation rests with the Court of Justice of the EU. This is not legal advice. Final classification decisions should involve qualified legal counsel with AI Act expertise. --- ## When to use this skill - The user has already concluded (via broad risk-tier triage or otherwise) that high-risk is the likely tier and needs the **depth assessment**. - A high-risk verdict is consequential (FRIA may apply, Chapter III conformity assessment regime, post-market monitoring, registration in EU databas

What's inside
Steps it walks through
  1. Disclaimer (show at session start, do not block)
  2. When to use this skill
  3. Effective dates (per AI Omnibus 2026)
  4. Required inputs
  5. Decision tree
  6. Step 1 — AI system gating (Art. 3(1))
  7. Step 2 — Intended-purpose framing (Art. 3(12); general principles ¶¶10–13)
  8. Step 3 — Art. 6(1) / Annex I branch
  9. Step 4 — Art. 6(2) / Annex III branch
  10. Step 5 — Art. 25 substantial-modification trap
  11. Output artefacts
  12. Artefact 1 — Structured decision block (terminal)
  13. Artefact 2 — Practitioner memo (1–2 page narrative)
  14. Artefact 3 — JSON interchange artefact
Ships with 19 files
  • LICENSE.txt
  • README.md
  • evals.json
  • references/ai-omnibus-timeline-postponements.md
  • references/annex-i-section-a-vs-b.md
  • references/annex-iii-area-1-biometrics.md
  • references/annex-iii-area-2-critical-infrastructure.md
  • references/annex-iii-area-3-education.md
  • references/annex-iii-area-4-employment.md
  • references/annex-iii-area-5-essential-services.md
  • references/annex-iii-area-6-law-enforcement.md
  • references/annex-iii-area-7-migration.md
  • references/annex-iii-area-8-justice-democracy.md
  • references/art-25-substantial-modification-flag.md
  • references/art-6-1-annex-i-guidelines.md
  • references/art-6-2-annex-iii-guidelines.md
  • references/art-6-3-exception-decision-tree.md
  • references/art-6-general-principles.md
  • references/safety-function-checklist.md
More from awesome-legal-skills
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About this skill
What does the eu-ai-act-high-risk-classifier-oliver-schmidt-prietz skill do?

Depth assessment of whether an AI system is high-risk under Art. 6 of the EU AI Act, grounded in the Commission's draft Art. 6(5) classification guidelines (general principles + Annex I + Annex III). Covers the Annex I product-safety route, all eight Annex III areas with worked examples, the Art. 6(3) exception and its profiling re-exception, and the Art. 25 quasi-provider trap. Outputs a structured decision block, a practitioner memo, and a JSON interchange artefact.

How do I install it?

Run `npx skills add lawve-ai/awesome-legal-skills --skill eu-ai-act-high-risk-classifier-oliver-schmidt-prietz --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From lawve-ai/awesome-legal-skills, a repository with 618 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going