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Conducts Privacy Impact Assessment for health data processing under GDPR Article 9, HIPAA, and sector-specific health privacy regulations. Covers special category data safeguards, clinical research data, patient portals, health wearables, genetic data, and cross-border health data transfers. Keywords: health data PIA, DPIA, Article 9, HIPAA, special category data, clinical research, patient privacy, genetic data.

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Oregon Consumer Privacy Act (OCPA) compliance. Unique provisions for de-identified data requirements, employee data partial exemption, nonprofit applicability, 14-day cure period, and consumer rights. Effective July 1, 2024. AG enforcement only.

日本語の概要は準備中です。原文の説明を表示しています。

Implements the GDPR Article 17 right to erasure (right to be forgotten) workflow, covering all six grounds for erasure, five exceptions, technical deletion versus anonymization decisions, and third-party notification under Article 19. Activate for erasure request, deletion request, right to be forgotten, Art. 17 queries.

日本語の概要は準備中です。原文の説明を表示しています。

Governs employee health data processing for fitness-for-work assessments, occupational health surveillance, COVID testing legacy programmes, and absence management. Applies Art. 9(2)(b) employment obligations and Art. 9(2)(h) health professional exceptions. Covers data minimisation, occupational health provider relationships, and return-to-work procedures. Keywords: health data, Art. 9, occupational health, fitness-for-work, special category, employment, sickness absence.

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Conducts a Data Protection Impact Assessment for automated decision-making and profiling systems under GDPR Article 35(3)(a), covering algorithmic transparency, meaningful human oversight, contestation mechanisms, and Art. 22 safeguards. Activate for DPIA automated decision, profiling DPIA, algorithmic impact assessment, Art. 35(3)(a), ADM risk assessment queries.

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Develops data classification policies with tiered handling (public, internal, confidential, restricted), labeling requirements, enforcement mechanisms, and procedures per tier. Covers policy governance, exception handling, and compliance monitoring. Keywords: classification policy, data tiers, handling procedures, labeling, enforcement, data governance, information security.

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Implements profiling restrictions for children under GDPR Recital 71, Article 22, UK AADC Standard 12, and COPPA. Covers prohibition of behavioural advertising to children, recommendation algorithm limitations, nudge technique prohibition, and automated decision-making safeguards. Keywords: profiling, children, behavioural advertising, recommendation algorithm, AADC, automated decision.

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Creates GDPR Article 30(1) Records of Processing Activities (RoPA) for data controllers with all seven mandatory fields: controller identity and contact details, processing purposes, data subject categories, personal data categories, recipient categories, third country transfers, and retention periods. Includes Python generator for automated RoPA creation. Activate for controller RoPA, Art. 30(1), processing records, data mapping.

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Guides DPIA for biometric processing systems including facial recognition, fingerprint, voice, iris, and gait analysis. Covers Art. 9 special category requirements, Art. 35(3)(b) mandatory DPIA triggers for large-scale biometric processing, and EDPB Guidelines 3/2019 on video surveillance. Keywords: biometric, facial recognition, fingerprint, DPIA, Art. 9, special category, EDPB Guidelines 3/2019.

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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.

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Algorithmic philosophies are computational aesthetic movements that are then expressed through code. Output .md files (philosophy), .html files (interactive viewer), and .js files (generative algorithms).

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Install and use the official AI Logo Maker package, pinned by digest, for paid hosted work on the Beatra service.

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Define go-to-market strategy including launch plan, messaging, channels, and timing during PRD v0.9 Go-to-Market. Triggers on requests to plan launch, define GTM strategy, or when user asks "how do we launch?", "go-to-market", "launch plan", "marketing strategy", "messaging", "launch channels", "GTM". Outputs GTM- entries with launch plan components.

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Use this skill when reasoning about generative AI, adversarial machine learning, neural network security, algorithmic fairness, or deep learning fundamentals. This skill channels the thinking of Ian Goodfellow, inventor of Generative Adversarial Networks (GANs). Trigger this skill when the user asks about model robustness, mitigating bias, evaluating AI guardrails, designing generative models, or defending against adversarial attacks. Apply his frameworks of minimax games, adversarial feature learning, and worst-case robustness analysis to shift the user's perspective from average-case optimization to adversarial resilience.

日本語の概要は準備中です。原文の説明を表示しています。

ArangoDB integration. Manage data, records, and automate workflows. Use when the user wants to interact with ArangoDB data.

日本語の概要は準備中です。原文の説明を表示しています。

Algorithmia integration. Manage data, records, and automate workflows. Use when the user wants to interact with Algorithmia data.

日本語の概要は準備中です。原文の説明を表示しています。

Algomo integration. Manage data, records, and automate workflows. Use when the user wants to interact with Algomo data.

日本語の概要は準備中です。原文の説明を表示しています。

Algolia Search integration. Manage Indexs, Records, Rules, Tasks, Clusters, Users. Use when the user wants to interact with Algolia Search data.

日本語の概要は準備中です。原文の説明を表示しています。

Algorand integration. Manage data, records, and automate workflows. Use when the user wants to interact with Algorand data.

日本語の概要は準備中です。原文の説明を表示しています。

Agora integration. Manage data, records, and automate workflows. Use when the user wants to interact with Agora data.

日本語の概要は準備中です。原文の説明を表示しています。

Prepare for contract negotiations with term analysis, BATNA preparation, negotiation playbooks, and comparison frameworks

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Extract language-agnostic pseudocode from formally verified programs (Isabelle/HOL, Coq) while preserving verified control flow, data dependencies, and algorithmic logic. Use when: (1) Users have verified code and need readable pseudocode, (2) Documenting verified algorithms for broader audiences, (3) Translating verified implementations to other languages, (4) Creating algorithm specifications from verified code, (5) Preserving verification guarantees in pseudocode form, or (6) Abstracting proof-heavy code to essential logic. Maintains semantic faithfulness to verified implementation.

日本語の概要は準備中です。原文の説明を表示しています。

Comprehensive design skill: brand identity, design tokens, UI styling, logo generation (55 styles, Gemini AI), corporate identity program (50 deliverables, CIP mockups), HTML presentations (Chart.js), banner design (22 styles, social/ads/web/print), icon design (15 styles, SVG, Gemini 3.1 Pro), social photos (HTML→screenshot, multi-platform). Actions: design logo, create CIP, generate mockups, build slides, design banner, generate icon, create social photos, social media images, brand identity, design system. Platforms: Facebook, Twitter, LinkedIn, YouTube, Instagram, Pinterest, TikTok, Threads, Google Ads.

日本語の概要は準備中です。原文の説明を表示しています。

Draft and explain persistent goal-loop prompts for long-running agent work with clear stop conditions.

日本語の概要は準備中です。原文の説明を表示しています。