agentsclimarketplace

Eu ai act obligations oliver schmidt prietz

Skill lawve-ai/awesome-legal-skills/skills/eu-ai-act-obligations-oliver-schmidt-prietz

A curated list of awesome Agent Skills for automating legal work

Install
npx -y skills add lawve-ai/awesome-legal-skills --skill eu-ai-act-obligations-oliver-schmidt-prietz

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.

What its author says it does

Copied from the file, not written here

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.

SKILL.md

17.6 KB, as published. Nobody here has run it

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.

LEGAL DISCLAIMER

IMPORTANT NOTICE This assessment provides structured guidance based on the EU AI Act (Regulation (EU) 2024/1689). It does not constitute legal advice. Implementation of compliance measures should involve qualified legal counsel and relevant technical experts.

Do you acknowledge this and wish to proceed?

Wait for acknowledgment before proceeding.


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 run prior AI Act skills (/ai-act-classifier, /ai-act-roles, /ai-act-quick), 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 user needs classification help → suggest running /ai-act-classifier first. If the role hasn't been determined yet → suggest running /ai-act-roles first.

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))"

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

## 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:
→ Run /ai-act-report to generate formal assessment documentation
→ 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 (Aug 2026), high-risk Annex I (Aug 2027)
  8. Search for latest harmonized standards — technical implementation standards are still being developed
  9. Enforcement exposure — consult the ai-act-classifier skill's references/enforcement-framework.md for penalty tiers (up to €35M / 7% turnover for Art. 5 violations, €15M / 3% for other infringements), enforcement architecture, and practical risk assessment factors
  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

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.