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israeli-ai-compliance-kit

Map Israeli and EU AI compliance obligations and generate model cards, data statements, and DPIA templates.

9|2|Updated Feb 23, 2026
Search Tags:#privacy#israel#dpia#model-card#ppl#eu-ai-act#ai-compliance
One-click install
npx skills add https://github.com/skills-il/security-compliance --skill israeli-ai-compliance-kit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: israeli-ai-compliance-kit
Source: https://github.com/skills-il/security-compliance/tree/main/israeli-ai-compliance-kit
Command: npx skills add https://github.com/skills-il/security-compliance --skill israeli-ai-compliance-kit

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Israeli ML teams face fragmented and evolving requirements from the Ministry of Innovation's voluntary AI principles, the Privacy Protection Law (PPL) and Amendment 13, multiple sector regulators, and the extraterritorial reach of the EU AI Act; this Skill consolidates scoping, mapping, templates, and operational guidance to avoid costly compliance gaps and accelerate enterprise reviews.

Core Features & Use Cases

  • Scoping & Classification: one-page scoping memo covering system type, personal data usage, EU exposure, and applicable Israeli sector regulators.
  • Regulatory Mapping: maps ML pipeline stages to PPL obligations (including Amendment 13), Data Security Regulations, and Ministry of Innovation 2023 principles to align controls with ethical and legal duties.
  • Artifact Generation & Tooling: model card and data statement guidance, DPIA templates, and scripts to generate model cards and classify EU AI Act risk for downstream documentation.
  • Sector Playbooks: targeted guidance for banking (BoI Directive 364), health (AMAR), insurance, transport, and defense/export controls.
  • Use Case: produce a model card, data statement, and DPIA for a Hebrew summarization API to satisfy a customer's AI risk review.

Quick Start

Run a scoping memo, then generate a model card and DPIA to satisfy an enterprise AI risk review.

Frequently Asked Questions about israeli-ai-compliance-kit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I map my ML pipeline to Israeli Privacy Protection Law and Amendment 13 obligations?▼

To map your ML pipeline to Israeli Privacy Protection Law (PPL) and Amendment 13, you align pipeline stages with specific PPL obligations and Data Security Regulations. This process ensures ML controls meet legal duties for personal data processing.

What is included in an AI compliance DPIA template for Israeli ML systems?▼

An AI compliance DPIA template for Israeli ML systems includes structured fields to assess privacy risks alongside Israeli-context model card and data statement guidance. It documents scoping memos and regulatory mappings to satisfy enterprise risk reviews.

Does this toolkit classify EU AI Act risk for Israeli ML teams?▼

Yes, the toolkit classifies EU AI Act risk for Israeli ML teams using included scripts. These scripts evaluate ML system exposure to extraterritorial EU regulations and generate model cards with specific Israeli-context fields for compliance documentation.

Can I generate a model card and data statement for a Hebrew NLP API?▼

Yes, you can generate a model card and data statement for a Hebrew NLP API. The toolkit provides artifact generation guidance and scripts to produce these documents, satisfying enterprise AI risk reviews and customer compliance requirements.

What is the best way to scope ML systems for Israeli sector regulators?▼

The best way to scope ML systems for Israeli sector regulators is to produce a one-page scoping memo. This memo identifies system type, personal data usage, EU exposure, and applicable regulators like banking (BoI Directive 364) or health (AMAR).

When do I need a scoping memo for AI governance and compliance?▼

You need a scoping memo for AI governance when initiating compliance reviews for ML systems targeting Israeli and EU markets. It identifies applicable sector regulators, EU AI Act exposure, and personal data usage before generating detailed model cards or DPIAs.

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