Agent skill

Eu AI Act Obligations Oliver Schmidt Prietz

by lawve-ai in lawve-ai/awesome-legal-skills

Maps the full set of legal obligations for the EU AI Act based on role + risk tier, producing an actionable compliance matrix with RACI assignments and implementation priorities.

AGPL-3.0Auto-check passedLegal & Compliance

Install Eu AI Act Obligations Oliver Schmidt Prietz

skills CLI
$ npx skills add lawve-ai/awesome-legal-skills --skill eu-ai-act-obligations-oliver-schmidt-prietz -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install lawve-ai/awesome-legal-skills eu-ai-act-obligations-oliver-schmidt-prietz --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/lawve-ai/awesome-legal-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/eu-ai-act-obligations-mapper-oliver-schmidt-prietz .claude/skills/eu-ai-act-obligations-oliver-schmidt-prietz && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
eu-ai-act-obligations-oliver-schmidt-prietz
GitHub stars
847
Token cost
~4.6k tokens
SKILL.md length
1,459 words
Files
20 (incl. references)
Skills in repo
154
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Maps the full set of legal obligations for the EU AI Act based on role + risk tier, producing an actionable compliance matrix with RACI assignments and implementation priorities.

  • Works in 4 steps: Input Context (Context-Aware Adaptive… → Obligation Mapping → Implementation Roadmap → …
  • Asks to map AI Act obligations
  • SKILL.md covers Disclaimer (show at session…, When to Search the Web, Workflow: Ask Questions ONE AT… and Critical Reminders, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Eu AI Act Obligations Oliver Schmidt Prietz is an agent skill from lawve-ai/awesome-legal-skills. Maps the full set of legal obligations for the EU AI Act based on role + risk tier, producing an actionable compliance matrix with RACI assignments and implementation priorities. This skill should be used when the user asks to "map AI Act obligations", "check what we need to do under the AI Act", "create a compliance checklist", "check deployer obligations", "assess provider duties", or mentions Art. 26, Art. 16-17, AI literacy Art. 4, DPIA, fundamental rights assessment, or "Pflichtenkatalog" under the AI Act.

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 20 other files, including reference files (for example `README.md`, `evals.json` and `references/art6-4-documentation.md`).

It sits in Legal & Compliance, covering AI governance. The repository describes itself as: A curated list of awesome Agent Skills for automating legal work. The licence is AGPL-3.0.

When your agent uses it

  • Asks to map AI Act obligations
  • Check what we need to do under the AI Act
  • Create a compliance checklist
  • Check deployer obligations

Example prompts

  • “map AI Act obligations”
  • “check what we need to do under the AI Act”
  • “create a compliance checklist”
  • “/eu-ai-act-obligations-oliver-schmidt-prietz”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Input Context (Context-Aware Adaptive Intake)
  2. Obligation Mapping
  3. Implementation Roadmap
  4. Obligations Matrix Output

What it can do on your machine

Read from SKILL.md and the folder at commit 045f738. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Eu AI Act Obligations Oliver Schmidt Prietz loads about 4.6k tokens when it runs, and up to ~56k if it reads all its reference files. Until then it costs about 140 tokens; SKILL.md has 1,459 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~140
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~56k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from lawve-ai/awesome-legal-skills at commit 045f738, republished under its AGPL-3.0 licence (© lawve-ai). 1,459 words, ~4,558 tokens.

Download SKILL.mdSave it as .claude/skills/eu-ai-act-obligations-oliver-schmidt-prietz/SKILL.md (or your agent's skills folder). This skill also uses 19 other files; get the full folder from GitHub.
name
eu-ai-act-obligations-oliver-schmidt-prietz
description
Maps the full set of legal obligations for the EU AI Act based on role + risk tier, producing an actionable compliance matrix with RACI assignments and implementation priorities. This skill should be used when the user asks to "map AI Act obligations", "check what we need to do under the AI Act", "create a compliance checklist", "check deployer obligations", "assess provider duties", or mentions Art. 26, Art. 16-17, AI literacy Art. 4, DPIA, fundamental rights assessment, or "Pflichtenkatalog" under the AI Act.
metadata.author
Oliver Schmidt-Prietz
metadata.license
AGPL-3.0
metadata.version
2026.06.05

EU AI Act Obligations Mapper

Map the full set of legal obligations based on role + risk tier under the AI Act (Regulation (EU) 2024/1689), producing an actionable compliance matrix with RACI assignments and implementation priorities.

Disclaimer (show at session start, do not block)

Important: This skill provides structured AI Act obligations guidance based on the EU AI Act (Regulation (EU) 2024/1689). It is not legal advice. Implementation of compliance measures should involve qualified legal counsel and relevant technical experts. Effective dates for high-risk obligations reflect the AI Omnibus 2026 postponement (Annex III: 2 December 2027; Annex I: 2 August 2028).


When to Search the Web

On activation — search for:

EU AI Act harmonized standards EN ISO implementing requirements [current year]
EU AI Act conformity assessment notified bodies guidance [current year]

For management systems — search for:

ISO 42001 AI management system alignment EU AI Act [current year]
EU AI Act quality management system requirements guidance

For national rules — search for:

[user's jurisdiction] AI Act national implementation measures [current year]
[user's jurisdiction] AI Act supervisory authority designation

For conformity assessment — search for:

EU AI Act conformity assessment procedures latest guidance
EU AI Act notified body designations [current year]

Workflow: Ask Questions ONE AT A TIME

Phase 1: Input Context (Context-Aware Adaptive Intake)

Step 1 — Context detection (always first):

"Let's map your AI Act obligations."

If you've already done a prior AI Act assessment (risk classification, role determination, or a quick triage), paste the Assessment Context block below. Otherwise, describe your situation in your own words.

Step 2 — Coverage analysis (internal — do not show this table to the user):

Map the context block or narrative to these 6 fields:

#FieldSource in context blockFallback
1Risk classification"Classification:" lineAsk
2Organizational role"Role:" lineAsk
3Organization size"Org Size:" lineAsk
4Sector"Sector:" lineAsk
5Jurisdiction(s)"Jurisdiction:" lineAsk
6Existing frameworksNot in context blockAlways ask

If the risk tier has not been classified yet → run a risk-tier classification first (AI-system test under Art. 3(1); prohibited / high-risk / GPAI / limited / minimal). If the role hasn't been determined yet → determine it first (provider / deployer / importer / distributor under Art. 3 and Art. 25).

Step 3 — Adaptive follow-up:

  • If context block provided → confirm extracted fields, then ask only about gaps. Fields 1-5 are typically covered; only field 6 (existing frameworks) needs asking.
  • If narrative provided → extract what's covered, ask about remaining gaps in a single grouped question.
  • If minimal information provided → ask about all missing fields in a single prompt, grouped conversationally.

Existing compliance status is always asked since it's new information not carried in the context block. Frame conversationally:

"One more thing — which compliance foundations do you already have in place? (Risk management, data quality, QMS, DPIA, incident reporting, AI literacy training, or starting from scratch)"

Maximum 2 interaction turns for intake. If a field remains unclear, mark as [UNCLEAR — proceeding with cautious assumptions].


Phase 2: Obligation Mapping

Based on role + risk tier, load the applicable obligation set.

Read the relevant reference files:

Deployer + High-Risk → Read references/high-risk-deployer-obligations.md Provider + High-Risk → Read references/high-risk-provider-obligations.md Any role + Low-Risk/Minimal → Read references/low-risk-obligations.md Non-high-risk Annex III (Art. 6(3) exception) → Read references/art6-4-documentation.md GPAI provider → Read references/gpai-obligations.md FRIA-triggering deployer → Read references/fria-template.md for Art. 27 FRIA methodology and fillable template Provider conformity assessment → Read references/conformity-assessment.md for Art. 43 track selection, EU Declaration, and CE marking Provider post-market monitoring → Read references/post-market-monitoring.md for Art. 72 monitoring system design and serious incident reporting EU database registration → Read references/eu-database-registration.md for Art. 49 registration process (provider and deployer tracks) All roles → Art. 4 AI competence obligation always applies

Obligation count preview:

"Based on your role as [Role] of a [risk tier] system, you have N obligations across K categories. I'll walk through them in 4 batches."

Batched assessment (4 batches replacing per-obligation questioning):

Present obligations grouped by category. For each batch, show a table with all obligations in that category and ask the user to respond to the entire batch at once:

BatchCategoryTypical obligations
1Technical MeasuresUse per instructions, monitoring, input data, log retention, data quality
2Organizational MeasuresOversight persons, inform affected persons, employee info, AI competence, incident reporting, registration, authority cooperation
3Management SystemsRisk management, data quality mgmt, QMS, post-market monitoring
4Impact AssessmentsDPIA, FRIA

For each batch, present a table:

Batch [X] of 4: [Category]

#ObligationLegal BasisPriorityStatus
1[obligation][article][Immediate/Short-term/Ongoing]Already in place / Partially addressed / Not yet addressed

"For each obligation, indicate: already in place, partially addressed, or not yet addressed. You can respond with just the numbers (e.g., '1,3 = in place; 2,4 = partial; 5 = not addressed')."

Progress indicator after each batch: "Batch [X] of 4 complete. [N] obligations remaining."

Smart defaults: If the user indicated "starting from scratch" in Phase 1, default all obligations to "not yet addressed" and confirm: "Since you're starting from scratch, I've marked all obligations as not yet addressed. Any exceptions?"

Target: 4-5 interaction turns instead of 20+.

Flag priority levels: critical timeline obligations first (e.g., Art. 26(6) 6-month log retention must be operational from day one).

GDPR Cross-Reference Checks

Read references/gdpr-crosswalk.md.

At relevant obligation points, suggest existing GDPR skills:

ObligationTriggerSuggestion
Art. 26(9) DPIAHigh-risk deployer"Perform a DPIA incorporating the provider's Art. 13 information about system capabilities and limitations"
Art. 26(11) inform affected personsDeployer transparency"Prepare a combined AI Act/GDPR transparency notice covering Art. 26(11) and Art. 13/14 GDPR"
Art. 10 data governanceProvider data quality"Conduct a data inventory review mapping AI training data against GDPR data quality and minimization principles"
Art. 26(7) employee informationWorkplace AI"Prepare employee AI transparency documentation combining Art. 26(7) and GDPR Art. 13/14 requirements"
Art. 26(5) serious incidentsIncident detected"Establish a dual incident reporting procedure covering both AI Act (Art. 73) and GDPR (Art. 33/34) timelines"
Personal data processingAny AI processing personal data"Review your GDPR Art. 28 processor agreement to include AI Act cooperation provisions (Art. 25(2))"
Show full SKILL.md (547 more words)Show less
Obligation Priority Decision Tree
         ┌─────────────────────────┐
         │ ROLE + RISK TIER        │
         └────────────┬────────────┘
                      │
    ┌─────────────────┼──────────────────┐
    │                 │                  │
    ▼                 ▼                  ▼
┌─────────┐   ┌──────────────┐   ┌──────────────┐
│ PROVIDER│   │   DEPLOYER   │   │ GPAI MODEL   │
│         │   │              │   │ PROVIDER     │
└────┬────┘   └──────┬───────┘   └──────┬───────┘
     │               │                  │
     ▼               ▼                  ▼
 High-Risk?      High-Risk?        Systemic Risk?
 ├─ YES:         ├─ YES:           ├─ YES:
 │ Art. 8-17     │ Art. 26         │ Art. 53 + 55
 │ Art. 17 QMS   │ Art. 27 FRIA    ├─ NO:
 │ Art. 9 Risk   │ Art. 26(9) DPIA │ Art. 53
 │ Art. 43 CA    │ Art. 49(3) Reg  └────────────
 │ Art. 49 Reg   └────────────
 │               ├─ NO (Art. 50):
 ├─ NO           │ Art. 50 only
 │ (Art. 50):    ├─ NO (Minimal):
 │ Art. 50       │ Art. 4 only
 │ +Art. 6(4)    └────────────
 │ if Annex III
 └────────────

 ALL ROLES: Art. 4 AI Competence (always applies)

For worked obligation mapping examples, see references/case-studies.md.


Phase 3: Implementation Roadmap

Group obligations by timeline:

1. IMMEDIATE (before deployment / already overdue if deployed):

  • Use system per operating instructions (Art. 26(1))
  • Monitoring system in place (Art. 26(5))
  • Qualified oversight persons assigned (Art. 26(2))
  • Log retention mechanism active (Art. 26(6))
  • AI competence measures (Art. 4)

2. SHORT-TERM (within 3 months of deployment):

  • Risk management system operational (Art. 9)
  • Data quality management (Art. 10)
  • Registration in EU database (Art. 49)
  • DPIA completed (Art. 26(9))
  • FRIA completed if required (Art. 27)
  • Employee information (Art. 26(7))

3. ONGOING (continuous):

  • System monitoring (Art. 26(5))
  • Logging and record-keeping (Art. 12, Art. 26(6))
  • Incident reporting (Art. 26(5) third sentence)
  • Authority cooperation (Art. 26(12))
  • Post-market monitoring data contribution

4. PERIODIC (regular intervals):

  • Risk reassessment (Art. 9 — recommended annually)
  • AI competence training updates (Art. 4)
  • Documentation review and update
  • Testing and validation (Art. 15)

Read references/technical-measures.md, references/organizational-measures.md, and references/management-systems.md for detailed requirements.

For the full compliance timeline with quarterly action calendar, resource estimates by organization size, and dependency mapping between activities, reference references/compliance-roadmap.md.


Phase 4: Obligations Matrix Output
markdown
## AI Act Compliance Obligations Matrix
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Role: [Role]  |  Risk Tier: [Tier]  |  Basis: [legal basis]
Organization: [name]  |  Date: [date]

### Technical Measures
| # | Obligation | Legal Basis | Priority | Status | RACI | Effort |
|---|-----------|-------------|----------|--------|------|--------|
| 1 | Use system per operating instructions | Art. 26(1) | Immediate | [ ] | IT=R, Legal=A | Low |
| 2 | Monitor system operation | Art. 26(5) | Immediate | [ ] | IT=R, Compliance=A | Medium |
| 3 | Ensure input data relevance | Art. 26(4) | Immediate | [ ] | IT=R, Business=A | Medium |
| 4 | Retain auto-generated logs (6 months) | Art. 26(6) | Immediate | [ ] | IT=R, Legal=A | Low |
| 5 | Data quality management | Art. 10 | Short-term | [ ] | IT=R, Data=A | High |

### Organizational Measures
| # | Obligation | Legal Basis | Priority | Status | RACI | Effort |
|---|-----------|-------------|----------|--------|------|--------|
| 1 | Assign qualified oversight persons | Art. 26(2) | Immediate | [ ] | HR=R, Legal=A | Medium |
| 2 | Inform affected persons | Art. 26(11) | Immediate | [ ] | Legal=R, Comms=A | Medium |
| 3 | Inform employees/works council | Art. 26(7) | Short-term | [ ] | HR=R, Legal=A | Medium |
| 4 | AI competence training | Art. 4 | Short-term | [ ] | HR=R, Mgmt=A | Medium |
| 5 | Incident reporting procedure | Art. 26(5) s.3 | Immediate | [ ] | Legal=R, IT=C | High |
| 6 | Register use in EU database | Art. 49(3) | Short-term | [ ] | Legal=R | Low |
| 7 | Cooperate with authorities | Art. 26(12) | Ongoing | [ ] | Legal=R, Mgmt=A | Low |

### Management Systems Required
| System | Legal Basis | Scope | Existing? |
|--------|------------|-------|-----------|
| Risk Management | Art. 9 | Continuous lifecycle risk assessment | [ ] |
| Data Quality Mgmt | Art. 10 | Training/validation/test data governance | [ ] |
| Quality Management | Art. 17 | Processes, procedures, compliance concept | [ ] |
| Post-Market Monitoring | Art. 72 | Monitoring throughout lifetime | [ ] |

### Impact Assessments Required
| Assessment | Legal Basis | When | Status |
|-----------|------------|------|--------|
| DPIA | Art. 26(9) + Art. 35 GDPR | Before deployment | [ ] |
| Fundamental Rights Assessment | Art. 27 | Before deployment (public bodies + certain private) | [ ] |

### GDPR Cross-References
| AI Act Obligation | GDPR Parallel | Recommended Action |
|------------------|---------------|----------------|
| Art. 26(9) DPIA | Art. 35 GDPR | Perform DPIA per Art. 35 GDPR incorporating Art. 13 information |
| Art. 26(11) inform persons | Art. 13/14 GDPR | Draft combined AI Act + GDPR transparency notice |
| Art. 10 data governance | Art. 25 GDPR (DPbD) | Conduct data inventory and governance review |
| Art. 26(7) employee info | Art. 13/14 GDPR | Prepare employee AI transparency documentation |
| Incident reporting | Art. 33/34 GDPR | Establish dual AI Act/GDPR incident reporting procedure |

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
SUMMARY:
TOTAL: [X] obligations | [Y] immediate | [Z] require legal judgment
Timeline: [X] already compliant | [Y] gaps identified | [Z] not yet assessed

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
ASSESSMENT CONTEXT (paste into next skill)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
System: [name]
Classification: [risk tier]
Basis: [legal basis]
Role: [role]
Quasi-Provider: [risk level]
Sector: [sector]
Jurisdiction: [list]
Org Size: [size]
Art. 50: [applicable triggers]
GPAI: [yes/no, systemic risk]

NEXT STEPS:
→ Generate formal assessment documentation (classification rationale + obligation matrix)
→ Address [Y] immediate gaps as priority
→ Establish management systems within [timeline]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Critical Reminders

  1. Art. 4 AI competence applies to ALL roles and ALL risk tiers — even minimal risk systems
  2. Art. 26(6) log retention (6 months) — must be in place from day one of deployment
  3. Art. 26(9) DPIA — must be completed BEFORE deployment, not after
  4. Art. 27 FRIA — required for public bodies, private entities providing public services, and deployers of insurance risk assessment (Annex III Nr. 5(b)) and social benefits eligibility (Annex III Nr. 5(c)) systems
  5. Art. 26(5) incident reporting — "without undue delay" to provider and authority
  6. SME proportionality — Art. 62 requires authorities to consider SME capabilities
  7. Transition periods vary — prohibited practices (Feb 2025), GPAI (Aug 2025), high-risk Annex III (Dec 2027 — Omnibus-postponed from Aug 2026), high-risk Annex I (Aug 2028 — Omnibus-postponed from Aug 2027). The AI Omnibus is a legislative-in-progress instrument; verify the current status of the postponement via a web search before relying on these dates.
  8. Search for latest harmonized standards — technical implementation standards are still being developed
  9. Enforcement exposure — factor in the penalty tiers when prioritising gaps: up to €35M / 7% of worldwide annual turnover for Art. 5 prohibited-practice violations, and €15M / 3% for other infringements (Art. 99). Enforcement runs through national market-surveillance authorities and, for GPAI, the AI Office.
  10. Jurisdiction-specific obligations — reference references/regulatory-overlays.md for per-country employment law, financial regulator, and data protection overlay requirements that apply in addition to AI Act obligations
  11. Compliance timeline & resources — reference references/compliance-roadmap.md for quarterly action calendar, resource estimation by organization size, and phased compliance roadmap template

Part of the EU AI Act suite

This skill works on its own, but it's designed to interlock with my other EU AI Act skills — install any individually, or use them together for an end-to-end workflow:

  • EU AI Act Quick Assessment — 15–25 min preliminary triage
  • EU AI Act System Classifier — risk-tier classification across all five tiers
  • EU AI Act High-Risk Classifier — depth Annex I / Annex III assessment
  • EU AI Act Role Determination — provider / deployer / importer / distributor (incl. Art. 25)
  • EU AI Act Examination Report Generator — audit-ready compliance report
  • EU AI Act Knowledge Base — Q&A over the Act + Commission guidelines

Each is available as a separate skill — install only what you need.

© lawve-ai, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 19 other files (references) in skills/eu-ai-act-obligations-mapper-oliver-schmidt-prietz of lawve-ai/awesome-legal-skills.

  • SKILL.md
  • LICENSE.txt
  • README.md
  • evals.json
  • references/art6-4-documentation.md
  • references/case-studies.md
  • references/compliance-roadmap.md
  • references/conformity-assessment.md
  • references/eu-database-registration.md
  • references/fria-template.md
  • references/gdpr-crosswalk.md
  • references/gpai-obligations.md
  • references/high-risk-deployer-obligations.md
  • references/high-risk-provider-obligations.md
  • references/low-risk-obligations.md
  • references/management-systems.md
  • references/organizational-measures.md
  • references/post-market-monitoring.md
  • references/regulatory-overlays.md
  • references/technical-measures.md

Open the folder on GitHubat commit 045f738

Compare with similar skills

Eu AI Act Obligations Oliver Schmidt Prietz next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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EU AI Act System Inventoryanthropics/claude-for-legal9.6k3 repos~2.8kAutomated safety check: PassApache-2.0
Eu AI Act Readinessseb1n/awesome-ai-agent-skills206—~3.3kAutomated safety check: PassMIT
AI GovernanceHack23/cia239—~1.4kAutomated safety check: PassApache-2.0

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Questions about Eu AI Act Obligations Oliver Schmidt Prietz

What does Eu AI Act Obligations Oliver Schmidt Prietz do?

Maps the full set of legal obligations for the EU AI Act based on role + risk tier, producing an actionable compliance matrix with RACI assignments and implementation priorities. Eu AI Act Obligations Oliver Schmidt Prietz is an agent skill from lawve-ai/awesome-legal-skills. Maps the full set of legal obligations for the EU AI Act based on role + risk tier, producing an actionable compliance matrix with RACI assignments and implementation priorities.

When should I use Eu AI Act Obligations Oliver Schmidt Prietz?

Eu AI Act Obligations Oliver Schmidt Prietz fits situations like: asks to map AI Act obligations; check what we need to do under the AI Act; create a compliance checklist; check deployer obligations.

How do I install Eu AI Act Obligations Oliver Schmidt Prietz in Claude Code?

Run `npx skills add lawve-ai/awesome-legal-skills --skill eu-ai-act-obligations-oliver-schmidt-prietz -a claude-code`. Or copy the skill folder (skills/eu-ai-act-obligations-mapper-oliver-schmidt-prietz in lawve-ai/awesome-legal-skills) into .claude/skills/eu-ai-act-obligations-oliver-schmidt-prietz in your project. Claude Code loads it when a task matches its description.

How do I install Eu AI Act Obligations Oliver Schmidt Prietz in Codex?

Run `npx skills add lawve-ai/awesome-legal-skills --skill eu-ai-act-obligations-oliver-schmidt-prietz -a codex`. Or copy the skill folder (skills/eu-ai-act-obligations-mapper-oliver-schmidt-prietz in lawve-ai/awesome-legal-skills) into .agents/skills/eu-ai-act-obligations-oliver-schmidt-prietz in your project. Codex loads it when a task matches its description.

Can I use Eu AI Act Obligations Oliver Schmidt Prietz in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add lawve-ai/awesome-legal-skills --skill eu-ai-act-obligations-oliver-schmidt-prietz -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/eu-ai-act-obligations-oliver-schmidt-prietz, .gemini/skills/eu-ai-act-obligations-oliver-schmidt-prietz, .github/skills/eu-ai-act-obligations-oliver-schmidt-prietz and .opencode/skills/eu-ai-act-obligations-oliver-schmidt-prietz in your project.

What does Eu AI Act Obligations Oliver Schmidt Prietz need to run?

SKILL.md names no scripts, command-line tools or credentials: Eu AI Act Obligations Oliver Schmidt Prietz is instructions for the agent only.

Does Eu AI Act Obligations Oliver Schmidt Prietz access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Eu AI Act Obligations Oliver Schmidt Prietz safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Eu AI Act Obligations Oliver Schmidt Prietz use?

Eu AI Act Obligations Oliver Schmidt Prietz is published under the AGPL-3.0 licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Eu AI Act Obligations Oliver Schmidt Prietz use?

About 4.6k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 51k tokens, read only when the agent opens those files.

What are the alternatives to Eu AI Act Obligations Oliver Schmidt Prietz?

Skills that share tags, products or a category with Eu AI Act Obligations Oliver Schmidt Prietz: Iso42001 (Sushegaad/Claude-Skills-Governance-Risk-and-Compliance, 946 stars), AI Risk Management (briiirussell/cybersecurity-skills, 413 stars), EU AI Act System Inventory (anthropics/claude-for-legal, 9.6k stars) and Eu AI Act Readiness (seb1n/awesome-ai-agent-skills, 206 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Eu AI Act Obligations Oliver Schmidt Prietz?

lawve-ai (a GitHub organization) maintains it in lawve-ai/awesome-legal-skills, which has 847 GitHub stars. The repository holds 154 skills in this directory. The repository was last updated on October 2, 2026.

Source: lawve-ai/awesome-legal-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.