Eu AI Act Specialist
alirezarezvani/claude-skills
EU AI Act (Regulation (EU) 2024/1689) operational compliance for compliance teams.
Preparing EU AI Act compliance documentation for high-risk AI systems.
Install AI Act High Risk Docs
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-act-high-risk-docs -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-act-high-risk-docs --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/privacy/ai-act-high-risk-docs .claude/skills/ai-act-high-risk-docs && rm -rf skills-srcUse ~/.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/
Install the "ai-act-high-risk-docs" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-act-high-risk-docs into .claude/skills/ai-act-high-risk-docs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-high-risk-docs", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-act-high-risk-docsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-act-high-risk-docs -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-act-high-risk-docs --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/privacy/ai-act-high-risk-docs .agents/skills/ai-act-high-risk-docs && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-act-high-risk-docs" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-act-high-risk-docs into .agents/skills/ai-act-high-risk-docs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-high-risk-docs", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-act-high-risk-docs -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-act-high-risk-docs --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/privacy/ai-act-high-risk-docs .cursor/skills/ai-act-high-risk-docs && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ai-act-high-risk-docs" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-act-high-risk-docs into .cursor/skills/ai-act-high-risk-docs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-high-risk-docs", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Privacy-Data-Protection-Skills.git --path skills/privacy/ai-act-high-risk-docs--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-act-high-risk-docs -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-act-high-risk-docs --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/privacy/ai-act-high-risk-docs .gemini/skills/ai-act-high-risk-docs && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ai-act-high-risk-docs" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-act-high-risk-docs into .gemini/skills/ai-act-high-risk-docs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-high-risk-docs", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-act-high-risk-docsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-act-high-risk-docs -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/privacy/ai-act-high-risk-docs .github/skills/ai-act-high-risk-docs && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ai-act-high-risk-docs" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-act-high-risk-docs into .github/skills/ai-act-high-risk-docs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-high-risk-docs", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-act-high-risk-docs -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-act-high-risk-docs --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/privacy/ai-act-high-risk-docs .opencode/skills/ai-act-high-risk-docs && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ai-act-high-risk-docs" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-act-high-risk-docs into .opencode/skills/ai-act-high-risk-docs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-high-risk-docs", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ai-act-high-risk-docs- GitHub stars
- 301
- Token cost
- ~2.4k tokens
- SKILL.md length
- 980 words
- Files
- 5 (incl. scripts, references, assets)
- Skills in repo
- 280
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Preparing EU AI Act compliance documentation for high-risk AI systems.
- Works in 10 steps: Verify quality management system is… → Prepare technical documentation per… → Conduct risk management assessment per… → …
- Tasks that involve AI governance
- SKILL.md covers Overview, High-Risk Classification, Technical Documentation… and Risk Management System (Art. 9), plus 4 more sections
- Runs Python scripts from its folder
What it does
AI Act High Risk Docs is an agent skill from mukul975/Privacy-Data-Protection-Skills. Preparing EU AI Act compliance documentation for high-risk AI systems. Covers Annex III classification, technical documentation under Art. 11, conformity assessment, risk management systems, and CE marking requirements. Keywords: EU AI Act, high-risk AI, Annex III, conformity assessment, CE marking.
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/standards.md` and `references/workflows.md`).
It sits in Legal & Compliance, covering AI governance and Technical documentation. The repository describes itself as: 282+ structured privacy & data protection skills for AI agents. GDPR, CCPA, EU AI Act, HIPAA, LGPD, PIPL, DPDP Act. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve AI governance
- Tasks that involve Technical documentation
Example prompts
- “/ai-act-high-risk-docs”
Requirements
- Python 3
Workflow steps
10 steps, taken from the first numbered list in SKILL.md.
- Verify quality management system is established (Art. 17)
- Prepare technical documentation per Annex IV
- Conduct risk management assessment per Art. 9
- Verify data governance per Art. 10
- Verify transparency and information provision per Art. 13
- Verify human oversight per Art. 14
- Verify accuracy, robustness, and cybersecurity per Art. 15
- Draw up EU Declaration of Conformity (Art. 47)
- Affix CE marking (Art. 48)
- Register in EU database (Art. 49)
What it can do on your machine
Read from SKILL.md and the folder at commit 9b2ef9e. 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
Ships 1 file in scripts/ (Python), which the agent can run.
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
AI Act High Risk Docs loads about 2.4k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 81 tokens; SKILL.md has 980 words of instructions outside code blocks.
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); the scripts in this folder are not scanned.
SKILL.md
The full file from mukul975/Privacy-Data-Protection-Skills at commit 9b2ef9e, republished under its Apache-2.0 licence (© mukul975). 980 words, ~2,448 tokens.
Download SKILL.mdSave it as
.claude/skills/ai-act-high-risk-docs/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- ai-act-high-risk-docs
- description
- Preparing EU AI Act compliance documentation for high-risk AI systems. Covers Annex III classification, technical documentation under Art. 11, conformity assessment, risk management systems, and CE marking requirements. Keywords: EU AI Act, high-risk AI, Annex III, conformity assessment, CE marking.
- license
- Apache-2.0
- metadata.author
- mukul975
- metadata.version
- 1.0
- metadata.domain
- privacy
- metadata.subdomain
- ai-privacy-governance
- metadata.tags
- eu-ai-act, high-risk-ai, annex-iii, conformity-assessment, technical-documentation
EU AI Act High-Risk AI System Documentation
Overview
The EU AI Act (Regulation 2024/1689, entered into force 1 August 2024, with high-risk obligations applicable from 2 August 2026) establishes a risk-based regulatory framework for artificial intelligence systems. High-risk AI systems — those listed in Annex III or used as safety components of products covered by Union harmonisation legislation in Annex I — must meet extensive documentation, transparency, and governance requirements before being placed on the EU market. Cerebrum AI Labs must prepare comprehensive technical documentation, implement a risk management system, ensure data governance, and undergo conformity assessment for each high-risk AI system.
High-Risk Classification
Annex III Categories Relevant to Cerebrum AI Labs
| Category | Annex III Reference | Cerebrum AI Labs System | Classification |
|---|---|---|---|
| Employment and workers management | Annex III, para. 4(a) | CV Screening AI — automated filtering of job applications | High-risk |
| Access to essential services | Annex III, para. 5(b) | Credit Scoring AI — creditworthiness assessment for financial products | High-risk |
| Law enforcement | Annex III, para. 6(a) | Not applicable | N/A |
| Biometric identification | Annex III, para. 1(a) | Facial Verification AI — identity verification at onboarding | High-risk |
| Education and vocational training | Annex III, para. 3(a) | Not applicable | N/A |
Classification Decision Tree
Is the AI system listed in Annex III?
├── Yes → High-risk (unless exception applies under Art. 6(3))
│ └── Does the system make decisions materially affecting natural persons?
│ ├── Yes → High-risk confirmed
│ └── No → May qualify for Art. 6(3) exception (narrow, profiling, preparatory)
│
├── No → Is it a safety component of a product under Annex I legislation?
│ ├── Yes → High-risk (subject to third-party conformity assessment)
│ └── No → Not high-risk under AI Act
│
└── Is it a general-purpose AI model with systemic risk? (Art. 51)
├── Yes → GPAI systemic risk obligations
└── No → GPAI transparency obligations onlyTechnical Documentation Requirements (Art. 11)
Annex IV — Required Documentation Content
Section 1: General Description
| Document Element | Content for Cerebrum AI Labs CV Screening AI |
|---|---|
| Intended purpose | Automated screening and ranking of job applications based on qualification match |
| Provider name and contact | Cerebrum AI Labs, 42 Innovation Drive, Dublin, Ireland |
| AI system version | v2.4.1 (deployed March 2026) |
| Hardware/software requirements | Cloud-hosted on EU infrastructure (AWS eu-west-1), Python 3.11, PyTorch 2.2 |
| Product integration | Integrated into Cerebrum TalentFlow ATS platform |
Section 2: Detailed Description of System Elements
| Element | Documentation Required |
|---|---|
| Development methodology | Model architecture, training approach, design choices and rationale |
| Computational resources | Training compute (GPU hours), energy consumption |
| Training data | Data sources, collection methods, size, labeling methodology, preprocessing |
| Validation and testing | Test datasets, metrics, results, known limitations |
| Input data specifications | Expected input format, quality requirements |
| Output description | Output format, confidence scores, decision thresholds |
Section 3: Monitoring, Functioning, and Control
| Element | Documentation Required |
|---|---|
| Human oversight measures | Art. 14 requirements: override capability, decision review process |
| Technical measures for accuracy | Accuracy metrics, drift detection, retraining triggers |
| Cybersecurity measures | Data encryption, access controls, adversarial robustness testing |
| Performance in edge cases | Known failure modes, boundary conditions, degradation behavior |
Section 4: Risk Management
| Element | Documentation Required |
|---|---|
| Risk management system | Art. 9 risk management process documentation |
| Known and foreseeable risks | Risk register with severity and likelihood |
| Mitigation measures | Controls for each identified risk |
| Residual risk assessment | Acceptable residual risk justification |
Risk Management System (Art. 9)
Continuous Risk Management Process for Cerebrum AI Labs
| Phase | Activity | Frequency |
|---|---|---|
| Identification | Identify risks to health, safety, and fundamental rights | Initial + quarterly |
| Analysis | Estimate risk severity and likelihood | Initial + quarterly |
| Evaluation | Compare risks against acceptance criteria | Initial + quarterly |
| Mitigation | Implement risk reduction measures | Ongoing |
| Monitoring | Track risk indicators in production | Continuous |
| Review | Review and update risk assessment | Quarterly |
Risk Register — CV Screening AI
| Risk ID | Risk Description | Severity | Likelihood | Mitigation | Residual Risk |
|---|---|---|---|---|---|
| R-001 | Gender bias in screening recommendations | High | Medium | Bias testing on protected attributes, debiasing training data | Low |
| R-002 | Discrimination against non-native language speakers | High | Medium | Multilingual evaluation, language-agnostic features | Medium |
| R-003 | Over-reliance on AI recommendations by recruiters | Medium | High | Mandatory human review, confidence thresholds | Low |
| R-004 | Inaccurate qualification matching for novel job roles | Medium | Medium | Fallback to keyword matching, human review flag | Low |
| R-005 | Privacy breach via training data memorization | High | Low | Differential privacy in training, memorization audit | Low |
Data Governance (Art. 10)
Show full SKILL.md (401 more words)Show less
Training Data Requirements
| Requirement | Implementation at Cerebrum AI Labs |
|---|---|
| Relevance and representativeness | Training data sourced from 50,000 job applications across 12 EU countries, balanced by gender, age, nationality |
| Bias examination | Statistical parity analysis on protected attributes (gender, age, ethnicity, disability) before and after training |
| Gap identification | Identified underrepresentation of applicants with disabilities; augmented with synthetic examples |
| Data quality | Automated data quality checks: completeness >95%, label accuracy >98% (human-verified sample) |
| Personal data processing | DPIA completed (DPIA-AI-2026-001); lawful basis: Art. 6(1)(f) legitimate interest; special categories removed |
Conformity Assessment (Art. 43)
Assessment Procedure for Cerebrum AI Labs
| System | Assessment Type | Basis |
|---|---|---|
| CV Screening AI | Internal conformity assessment (Art. 43(2)) + quality management system | Annex III, para. 4 — not biometric, not critical infrastructure |
| Credit Scoring AI | Internal conformity assessment (Art. 43(2)) | Annex III, para. 5 |
| Facial Verification AI | Third-party conformity assessment (Art. 43(1)) via notified body | Annex III, para. 1 — biometric identification |
Internal Conformity Assessment Steps
- Verify quality management system is established (Art. 17)
- Prepare technical documentation per Annex IV
- Conduct risk management assessment per Art. 9
- Verify data governance per Art. 10
- Verify transparency and information provision per Art. 13
- Verify human oversight per Art. 14
- Verify accuracy, robustness, and cybersecurity per Art. 15
- Draw up EU Declaration of Conformity (Art. 47)
- Affix CE marking (Art. 48)
- Register in EU database (Art. 49)
Post-Market Monitoring (Art. 72)
| Activity | Frequency | Owner |
|---|---|---|
| Performance metric monitoring | Continuous | ML Engineering |
| Bias drift detection | Weekly | Responsible AI team |
| Incident reporting | As needed (within 15 days for serious incidents per Art. 73) | DPO + Legal |
| User feedback collection | Continuous | Product team |
| Risk register update | Quarterly | Risk Management |
| Technical documentation update | On material change | ML Engineering + Legal |
Key Legal References
- EU AI Act (Regulation 2024/1689) — Full text, entered into force 1 August 2024
- AI Act Art. 6 + Annex III — High-risk classification criteria
- AI Act Art. 9 — Risk management system requirements
- AI Act Art. 10 — Data and data governance requirements
- AI Act Art. 11 + Annex IV — Technical documentation requirements
- AI Act Art. 13 — Transparency and provision of information to deployers
- AI Act Art. 14 — Human oversight requirements
- AI Act Art. 43 — Conformity assessment procedures
- AI Act Art. 72 — Post-market monitoring obligations
- AI Act Art. 73 — Reporting of serious incidents
- GDPR Art. 22 — Automated individual decision-making (complementary to AI Act)
- EDPB-EDPS Joint Opinion 5/2021 on the AI Act Proposal — Data protection perspective on AI regulation
© mukul975, Apache-2.0. 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 4 other files (scripts, references, assets) in skills/privacy/ai-act-high-risk-docs of mukul975/Privacy-Data-Protection-Skills.
- SKILL.md
- assets/template.md
- references/standards.md
- references/workflows.md
- scripts/process.py
Open the folder on GitHubat commit 9b2ef9e
Compare with similar skills
AI Act High Risk Docs 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AI Act High Risk Docs this skillmukul975/Privacy-Data-Protection-Skills | 301 | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Eu AI Act Specialistalirezarezvani/claude-skills | 28k | — | ~3.7k | Automated safety check: Pass | MIT | |
| Iso42001Sushegaad/Claude-Skills-Governance-Risk-and-Compliance | 946 | 1 repos | ~3.7k | Automated safety check: Pass | MIT | |
| AI Risk Managementbriiirussell/cybersecurity-skills | 413 | — | ~3.7k | Automated safety check: Notes | MIT | |
| EU AI Act System Inventoryanthropics/claude-for-legal | 9.6k | 3 repos | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Eu AI Act Readinessseb1n/awesome-ai-agent-skills | 206 | — | ~3.3k | Automated safety check: Pass | MIT |
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Categories
Questions about AI Act High Risk Docs
What does AI Act High Risk Docs do?
Preparing EU AI Act compliance documentation for high-risk AI systems. AI Act High Risk Docs is an agent skill from mukul975/Privacy-Data-Protection-Skills. Preparing EU AI Act compliance documentation for high-risk AI systems.
When should I use AI Act High Risk Docs?
AI Act High Risk Docs fits situations like: tasks that involve AI governance; tasks that involve Technical documentation.
How do I install AI Act High Risk Docs in Claude Code?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-act-high-risk-docs -a claude-code`. Or copy the skill folder (skills/privacy/ai-act-high-risk-docs in mukul975/Privacy-Data-Protection-Skills) into .claude/skills/ai-act-high-risk-docs in your project. Claude Code loads it when a task matches its description.
How do I install AI Act High Risk Docs in Codex?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-act-high-risk-docs -a codex`. Or copy the skill folder (skills/privacy/ai-act-high-risk-docs in mukul975/Privacy-Data-Protection-Skills) into .agents/skills/ai-act-high-risk-docs in your project. Codex loads it when a task matches its description.
Can I use AI Act High Risk Docs 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 mukul975/Privacy-Data-Protection-Skills --skill ai-act-high-risk-docs -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-act-high-risk-docs, .gemini/skills/ai-act-high-risk-docs, .github/skills/ai-act-high-risk-docs and .opencode/skills/ai-act-high-risk-docs in your project.
What does AI Act High Risk Docs need to run?
Going by SKILL.md and its folder, AI Act High Risk Docs needs Python for the scripts in its folder. Our summary lists: Python 3.
Does AI Act High Risk Docs 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 AI Act High Risk Docs 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does AI Act High Risk Docs use?
AI Act High Risk Docs is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does AI Act High Risk Docs use?
About 2.4k tokens (SKILL.md is roughly 9.8k 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 1.5k tokens, read only when the agent opens those files.
What are the alternatives to AI Act High Risk Docs?
Skills that share tags, products or a category with AI Act High Risk Docs: Eu AI Act Specialist (alirezarezvani/claude-skills, 28k stars), Iso42001 (Sushegaad/Claude-Skills-Governance-Risk-and-Compliance, 946 stars), AI Risk Management (briiirussell/cybersecurity-skills, 413 stars) and EU AI Act System Inventory (anthropics/claude-for-legal, 9.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Act High Risk Docs?
mukul975 (a GitHub user) maintains it in mukul975/Privacy-Data-Protection-Skills, which has 301 GitHub stars. The repository holds 280 skills in this directory. The repository was last updated on March 16, 2026.
Source: mukul975/Privacy-Data-Protection-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.