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概要と使いどころ
Complete guide to LINDDUN privacy threat modeling methodology covering seven threat categories: Linking, Identifying, Non-repudiation, Detecting, Data Disclosure, Unawareness, and Non-compliance. Includes DFD-based analysis, threat tree catalogs, mitigation mapping to privacy design patterns, and step-by-step process.
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Guides continuous privacy compliance monitoring implementation including automated control testing, evidence collection automation, real-time compliance dashboards, alert-based remediation workflows, regulatory change integration, and deviation management. Covers GRC platform configuration, control framework mapping, and compliance-as-code approaches. Keywords: continuous compliance, automated monitoring, evidence collection, dashboard, regulatory change, compliance-as-code.
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Implementing cookie compliance across multiple jurisdictions including EU ePrivacy Directive, UK PECR, US California CCPA/CPRA opt-out model, and Brazil LGPD. Provides a requirements matrix and geolocation-based implementation approach.
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Compares PIA/DPIA methodologies: CNIL PIA tool, ICO DPIA template, NIST Privacy Framework, and ISO 29134. Provides methodology selection criteria based on regulatory jurisdiction, organisation maturity, processing complexity, and resource availability. Covers regulatory acceptance, tool features, and cross-methodology mapping. Keywords: PIA methodology, CNIL, ICO, NIST Privacy Framework, ISO 29134, DPIA comparison, assessment.
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Implements Children's Online Privacy Protection Act (COPPA) compliance under 16 CFR Part 312. Covers verifiable parental consent methods including signed forms, credit card verification, government ID, knowledge-based authentication, and video call. Includes FTC safe harbor programs and enforcement actions. Keywords: COPPA, FTC, children, parental consent, safe harbor, verifiable consent.
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Automated enforcement of GDPR Article 5(1)(e) storage limitation principle. Covers TTL-based deletion, retention policy engines, archival workflows, legal hold exemptions, and lifecycle automation. Includes technical implementation patterns for automated data expiry and defensible deletion across distributed systems.
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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.
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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.
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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.
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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.
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Manages privacy compliance for employee background checks including criminal record processing under Art. 10 GDPR, DBS checks (UK), national law variations, and reference verification. Applies proportionality and data minimisation to pre-employment screening, defines retention limits, and addresses role-based necessity assessments. Keywords: background check, criminal record, Art. 10, DBS, pre-employment screening, vetting, data minimisation, proportionality.
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AWS serverless and event-driven architecture expert based on Well-Architected Framework. Use when building serverless APIs, Lambda functions, REST APIs, microservices, or async workflows.
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。
Validates whether an API request is correct based on provided inputs (method, URL, headers, body, auth, query params).
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Core UI/UX engineering skill for building highly interactive, spatial, weightless, and glassmorphism-based web interfaces using GSAP and 3D CSS.
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Diff a live page's accessibility violations against a baseline — by default compares uncommitted changes (stash-based), or pass --branch [<name>] to diff against a branch. Reports only new violations introduced, violations fixed, and pre-existing count. Use `scan` for a full audit with no diffing.
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Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
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Use when configuring Spring Boot as an OAuth2 resource server, validating JWTs from an external auth provider (Keycloak, Auth0, Okta, Cognito), extracting claims, or implementing scope-based authorization.
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Scene composition and orchestration skill for creating complex multi-part animations. **Triggers when:** - User wants to compose multi-element scenes - Request involves combining multiple visual elements - Scene requires act-based structure or transitions - User mentions "scene", "compose", "combine", "orchestrate" **Capabilities:** - Scene graph construction with acts and transitions - Multi-object coordination and timing - Camera movements and focus control - Layered animation sequences
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。
Use when retrieving the most relevant skills from a local or private skill library instead of relying on network-based skill discovery.
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。
Modern Go Web application architecture guide. Use when creating new Go web projects, APIs, or microservices. Covers project structure, tech stack selection, and best practices based on Go standards.
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Ask Grok or Gemini via opencli (browser-session based, no API cost). Use when the user says "问 grok", "问 gemini", "ask grok", "ask gemini", "用 grok 查", "grok 怎么看", "让 gemini 分析", or wants a second opinion from Grok/Gemini without paying API tokens. Routes to opencli which drives the already-logged-in Chrome session.
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Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
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Comprehensive guide for Slidev - a web-based presentation framework for developers. Covers Markdown syntax, layouts, components, animations, theming, and exporting. Use this skill when creating or working with developer presentations using Slidev.
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Create beautiful infographics based on the given text content. Use this when users request creating infographics.
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。