Privacy-Data-Protection-Skills

In the author's own words, from each skill's SKILL.md — showing the first 30 of 824 files.

• 42-cfr-part-2

  Implements 42 CFR Part 2 protections for substance use disorder patient records. Covers written consent requirements stricter than HIPAA, re-disclosure prohibition, court order procedures, qualified service organization agreements, and 2024 amendments aligning Part 2 with HIPAA. Keywords: 42 CFR Part 2, substance use disorder, SUD records, re-disclosure, consent, Part 2 amendments.

  skills/privacy/42-cfr-part-2/SKILL.md on GitHub (opens in a new tab)

• adequacy-assessment

  Guides assessment of third-country adequacy decisions under GDPR Article 45 for international data transfers. Covers the current EC adequacy decisions list, adequacy assessment criteria, partial adequacy handling, and monitoring of adequacy decision reviews. Keywords: adequacy decision, Article 45, third country, adequate protection, EC adequacy list.

  skills/privacy/adequacy-assessment/SKILL.md on GitHub (opens in a new tab)

• age-gating-services

  Implements age-gating mechanisms for online services to restrict access based on user age. Covers hard gates versus soft gates, neutral age prompts, re-verification triggers, circumvention prevention, and regulatory requirements under GDPR, COPPA, UK Online Safety Act, and DSA. Keywords: age gate, age restriction, neutral prompt, children, online services, access control.

  skills/privacy/age-gating-services/SKILL.md on GitHub (opens in a new tab)

• age-verification-methods

  Evaluates and implements age estimation and verification technologies for online services. Covers facial age estimation, digital ID verification, self-declaration with risk assessment, AI-based age estimation, and the accuracy versus privacy tradeoff. Includes ICO guidance and euCONSENT framework. Keywords: age verification, age estimation, facial analysis, digital ID, children, online safety.

  skills/privacy/age-verification-methods/SKILL.md on GitHub (opens in a new tab)

• ai-act-high-risk-docs

  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.

  skills/privacy/ai-act-high-risk-docs/SKILL.md on GitHub (opens in a new tab)

• ai-automated-decisions

  Implements GDPR Art. 22 automated decision-making and AI Act Art. 14 human oversight requirements for AI systems. Covers identification of solely automated decisions, meaningful human intervention design, logic explanation mechanisms, and contestation procedures. Keywords: Art. 22, automated decision, human oversight, AI Act, profiling, contestation.

  skills/privacy/ai-automated-decisions/SKILL.md on GitHub (opens in a new tab)

• ai-bias-special-category

  Assesses AI bias risks for GDPR Art. 9 special category data and AI Act Art. 10 data governance. Covers fairness metrics, bias detection methods, mitigation strategies, and documentation requirements for protected characteristics. Keywords: AI bias, special category, fairness metrics, discrimination, Art. 9, Art. 10.

  skills/privacy/ai-bias-special-category/SKILL.md on GitHub (opens in a new tab)

• ai-data-retention

  Manages AI model retention and machine unlearning requirements. Covers training data deletion verification, model versioning for compliance, machine unlearning techniques (SISA, gradient-based), and retraining triggers. Keywords: AI retention, machine unlearning, model versioning, training data deletion, retraining, storage limitation.

  skills/privacy/ai-data-retention/SKILL.md on GitHub (opens in a new tab)

• ai-data-subject-rights

  Implements data subject rights mechanisms for AI systems including right to explanation of AI decisions, contestation procedures, human review, model output correction, and training data access. Covers GDPR Arts. 15-22 and AI Act Art. 86. Keywords: data subject rights, AI explanation, contestation, human review, training data access, model correction.

  skills/privacy/ai-data-subject-rights/SKILL.md on GitHub (opens in a new tab)

• ai-deployment-checklist

  Pre-deployment privacy compliance checklist for AI/ML systems covering DPIA completion, lawful basis verification, transparency notices, human oversight mechanisms, bias testing, and post-deployment monitoring setup. Keywords: AI deployment, privacy checklist, go-live, model deployment, compliance gate.

  skills/privacy/ai-deployment-checklist/SKILL.md on GitHub (opens in a new tab)

• ai-dpia

  Conducts Data Protection Impact Assessments for AI and ML systems per EDPB Guidelines 04/2025 on AI processing. Covers training data lawfulness evaluation, model risk assessment, automated decision triggers, and AI-specific DPIA methodology. Keywords: AI DPIA, machine learning impact assessment, EDPB AI guidelines, model risk, training data.

  skills/privacy/ai-dpia/SKILL.md on GitHub (opens in a new tab)

• ai-federated-learning

  Implements federated learning architecture patterns for GDPR compliance. Covers secure aggregation protocols, differential privacy integration, communication protocols, and privacy-by-design distributed ML training. Keywords: federated learning, distributed training, secure aggregation, differential privacy, privacy-preserving ML.

  skills/privacy/ai-federated-learning/SKILL.md on GitHub (opens in a new tab)

• ai-model-privacy-audit

  Conducts privacy auditing of AI models including training data extraction testing, membership inference attacks, model inversion testing, and attribute inference assessment. Uses ML Privacy Meter and related tools to quantify privacy leakage. Keywords: model audit, membership inference, privacy meter, model inversion, training data extraction.

  skills/privacy/ai-model-privacy-audit/SKILL.md on GitHub (opens in a new tab)

• ai-privacy-assessment

  Guides the combined DPIA and AI Act conformity assessment for AI systems processing personal data. Covers EDPB-EDPS Joint Opinion 5/2021, training data lawfulness under Art. 6 and Art. 9, Art. 22 automated decision-making, algorithmic bias detection, and NIST AI RMF MAP function. Keywords: AI privacy, DPIA, AI Act, algorithmic bias, automated decision-making, Art. 22, training data, NIST AI RMF.

  skills/privacy/ai-privacy-assessment/SKILL.md on GitHub (opens in a new tab)

• ai-privacy-impact-template

  Provides combined DPIA and AI Act conformity assessment template with integrated risk scoring matrix. Covers GDPR Art. 35 DPIA elements, AI Act high-risk system requirements, mitigation measures, and human oversight assessment. Keywords: DPIA template, conformity assessment, risk scoring, AI Act, combined assessment, high-risk AI.

  skills/privacy/ai-privacy-impact-template/SKILL.md on GitHub (opens in a new tab)

• ai-privacy-inference

  Managing privacy risks from AI-driven inferences about individuals including derived data classification, profiling under GDPR Art. 22, inference accuracy obligations, and controlling automated personality/behaviour predictions. Keywords: AI inference, derived data, profiling, automated predictions, GDPR.

  skills/privacy/ai-privacy-inference/SKILL.md on GitHub (opens in a new tab)

• ai-training-data-class

  Classifies sensitive data in AI/ML training datasets including bias detection for Art. 9 categories, data card documentation, provenance tracking, and consent verification for model training. Keywords: AI training data, ML dataset, bias detection, data card, model training, Art 9, consent, GDPR AI.

  skills/privacy/ai-training-data-class/SKILL.md on GitHub (opens in a new tab)

• ai-training-lawfulness

  Assesses lawful basis for AI training data processing per EDPB April 2025 report on LLMs and general-purpose AI. Covers legitimate interest balancing tests, consent challenges for ML training, public dataset assessment, and web scraping lawfulness. Keywords: AI training data, lawful basis, EDPB LLM, legitimate interest, consent, web scraping.

  skills/privacy/ai-training-lawfulness/SKILL.md on GitHub (opens in a new tab)

• ai-transparency-reqs

  Implements AI transparency requirements under EU AI Act Arts. 13-14 and GDPR Arts. 13-14. Covers user notification of AI interaction, system capability disclosure, limitation documentation, and meaningful information about automated logic. Keywords: AI transparency, EU AI Act, GDPR notification, explainability, automated decision.

  skills/privacy/ai-transparency-reqs/SKILL.md on GitHub (opens in a new tab)

• ai-vendor-privacy-due

  Determines controller-processor relationships for AI services and conducts privacy due diligence. Covers SaaS AI (processor), embedded AI (joint controller), API-based AI (assessment framework), and vendor risk assessment. Keywords: AI vendor, controller-processor, due diligence, SaaS AI, joint controller, Art. 28.

  skills/privacy/ai-vendor-privacy-due/SKILL.md on GitHub (opens in a new tab)

• analytics-cookie-consent

  Managing consent for analytics cookies and implementing privacy-preserving measurement. Covers GA4 privacy configuration, consent mode fallback behavior, aggregate reporting alternatives, and cookieless measurement approaches.

  skills/privacy/analytics-cookie-consent/SKILL.md on GitHub (opens in a new tab)

• anonymization-alternative

  Evaluates anonymization as a retention alternative under GDPR Recital 26, applying the WP29 Opinion 05/2014 techniques including randomization and generalization. Validates anonymization effectiveness using k-anonymity, l-diversity, and t-closeness metrics. Activate for anonymization, de-identification, k-anonymity, retention alternative queries.

  skills/privacy/anonymization-alternative/SKILL.md on GitHub (opens in a new tab)

• apac-transfers

  Guides management of cross-border data transfers under Asia-Pacific regulatory frameworks including APEC CBPR, ASEAN Model Contractual Clauses, Japan APPI supplementary rules, South Korea PIPA provisions, and Thailand/Singapore PDPA mechanisms. Keywords: APEC CBPR, ASEAN MCCs, APPI, PIPA, PDPA, APAC transfers.

  skills/privacy/apac-transfers/SKILL.md on GitHub (opens in a new tab)

• apec-cbpr-cert

  Guides APEC Cross-Border Privacy Rules system certification process including self-assessment against the APEC Privacy Framework principles, accountability agent selection, intake questionnaire completion, certification decision, annual recertification, and Global CBPR Forum transition. Keywords: APEC, CBPR, cross-border privacy, accountability agent, certification, Global CBPR.

  skills/privacy/apec-cbpr-cert/SKILL.md on GitHub (opens in a new tab)

• applying-privacy-design-patterns

  Systematic application of the eight privacy design patterns per Hoepman: minimize, hide, separate, abstract, inform, control, enforce, and demonstrate. Covers pattern selection methodology per processing activity, mapping to GDPR principles, and practical implementation guidance for privacy-by-design system architecture.

  skills/privacy/applying-privacy-design-patterns/SKILL.md on GitHub (opens in a new tab)

• art49-derogations

  Guides assessment and application of GDPR Article 49 derogation conditions for international data transfers in the absence of adequacy decisions or appropriate safeguards. Covers explicit consent, contract necessity, public interest, vital interests, public register, and compelling legitimate interests with restrictive interpretation per EDPB Guidelines 2/2018. Keywords: Art. 49, derogations, tra…

  skills/privacy/art49-derogations/SKILL.md on GitHub (opens in a new tab)

• audit-evidence-collect

  Guides privacy audit evidence collection processes including evidence planning, sampling strategies, documentation standards, chain of custody, interview techniques, system walkthrough procedures, and evidence evaluation. Covers ISO 19011 evidence categories (records, statements of fact, observations) and ISACA audit evidence requirements for privacy compliance assessments. Keywords: audit eviden…

  skills/privacy/audit-evidence-collect/SKILL.md on GitHub (opens in a new tab)

• audit-follow-up-verify

  Guides audit follow-up and verification processes including follow-up scheduling, remediation effectiveness testing, finding closure criteria, re-testing procedures, status reporting, and escalation of unremediated findings. Implements IIA Standard 2500 monitoring requirements and ISO 19011 follow-up guidance for privacy audit engagements. Keywords: audit follow-up, verification testing, finding…

  skills/privacy/audit-follow-up-verify/SKILL.md on GitHub (opens in a new tab)

• audit-remediation-program

  Guides audit findings remediation program management including finding prioritization by severity (critical, high, medium, low), owner assignment, remediation planning, deadline tracking, verification testing, closure criteria, escalation protocols, and management reporting. Covers remediation lifecycle from finding issuance to verified closure. Keywords: audit remediation, finding management, pr…

  skills/privacy/audit-remediation-program/SKILL.md on GitHub (opens in a new tab)

• audit-report-writing

  Guides privacy audit report writing including executive summary drafting, findings classification (critical, high, medium, low), evidence referencing, root cause analysis documentation, recommendation formulation, management response tracking, and report distribution protocols. Covers report structure from scope definition through appendices and sign-off. Keywords: audit report, findings document…

  skills/privacy/audit-report-writing/SKILL.md on GitHub (opens in a new tab)

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