「regulations」の検索結果

Use when reviewing, designing, or modifying Java enterprise systems that process personal data and need GDPR-aware engineering controls. This should trigger for requests such as Review a Java service for GDPR privacy controls; Design data-subject rights workflows; Add retention, deletion, pseudonymization, or privacy-safe logging; Assess data transfer, DPIA, breach evidence, or processor/controller boundary concerns before production release. Part of Plinth Toolkit

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 reviewing, designing, or modifying Java enterprise systems from a maintainer-authored or maintainer-sanitized NIS2 engineering evidence inventory. Supports essential or important entities, critical-sector services, managed service providers, supply-chain dependencies, and cybersecurity incident escalation obligations without ingesting raw code, logs, runbooks, tickets, provider documents, or other operational free text. Part of Plinth Toolkit

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 reviewing, designing, or modifying Java enterprise software products, AI-enabled products, RAG assistants, AI agents, generated instructions, related services, automated updates, vulnerability handling, corrective updates, warnings, instructions, or product-safety evidence under Directive (EU) 2024/2853, the EU Product Liability Directive. Part of Plinth Toolkit

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 reviewing, designing, or modifying Java enterprise systems and need a structured, repeatable ISO/IEC 25010:2023 quality-attribute review covering Functional Suitability, Performance Efficiency, Compatibility, Interaction Capability, Reliability, Security, Maintainability, Flexibility, and Safety, producing an engineering review report rather than an interactive ADR discovery. Part of Plinth Toolkit

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 reviewing, designing, or modifying Java enterprise systems that expose, exchange, store, process, export, or port data across users, businesses, connected products, cloud providers, APIs, event streams, AI data pipelines, data spaces, or SaaS platforms and need EU Data Act engineering controls. This should trigger for requests such as Review a Java platform for EU Data Act controls; Design data access and portability evidence; Add data-sharing request workflows, export formats, interoperability, metadata, audit logs, cloud-switching support, non-personal data safeguards, or trade-secret handoffs; Assess Data Act engineering readiness before production release. Part of Plinth Toolkit

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 reviewing, designing, or modifying Java enterprise systems that may support intermediary services, hosting services, online platforms, marketplaces, content moderation, recommender systems, advertising delivery, complaint workflows, transparency reporting, or systemic-risk evidence under the EU Digital Services Act. This should trigger for requests such as Review a Java online platform for DSA controls; Design notice-and-action or appeal workflows; Add recommender, ad transparency, moderation, audit, researcher access, or privacy-safe observability evidence; Assess online-platform transparency controls before production release. Part of Plinth Toolkit

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 reviewing, designing, or modifying Java enterprise systems that may support EU Market Abuse Regulation concerns, market surveillance, suspicious order and transaction reports, insider dealing controls, unlawful disclosure controls, market manipulation detection, inside information disclosure workflows, insider-list evidence, PDMR transaction notifications, alert explainability, model or rule provenance, reviewer decisions, or compliance escalation. This should trigger for requests such as Review a Java trading surveillance system for MAR controls; Design suspicious order and transaction monitoring evidence; Add alert explainability and reviewer-decision audit trails; Assess AI-assisted market-abuse detection before production release. Part of Plinth Toolkit

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 reviewing, designing, or modifying Java enterprise systems that use GenAI, LLMs, AI-assisted coding, RAG, AI agents, generated code, generated dependencies, prompt workflows, external model providers, or AI-enabled business logic and need ISO/IEC 42001 AI management system-aware engineering guidance. Part of Plinth Toolkit

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 reviewing Java enterprise evidence for MiFID II investment services, investment activities, client classification, suitability, appropriateness, order-handling evidence, best-execution evidence, algorithmic-trading governance evidence, market-access governance evidence, transaction evidence, record keeping, monitoring, or compliance-owner handoff. This should trigger for requests such as Review a Java investment-service platform for MiFID II evidence; Assess suitability, appropriateness, order-handling evidence, or best-execution evidence; Document audit, monitoring, or clock-synchronisation gaps for algorithmic-trading governance; Assess investment-service engineering evidence before production release. Part of Plinth Toolkit

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 reviewing, designing, or modifying Java enterprise systems that may support EU Digital Markets Act gatekeeper-platform concerns, core platform services, interoperability, business-user data access, consent-dependent data combination, ranking, self-preferencing, advertising transparency, or anti-circumvention controls. This should trigger for requests such as Review a Java platform for DMA controls; Design interoperability and business-user data access evidence; Add ranking, consent, preference, or anti-circumvention audit controls; Assess gatekeeper-platform engineering evidence before production release. Part of Plinth Toolkit

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。

Automated safety compliance verification for construction sites. Check PPE usage, zone access, working at heights regulations, and generate compliance reports using rule-based and ML approaches.

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 compliance with the UAE Federal Decree-Law No. 45 of 2021 on the Protection of Personal Data (UAE PDP Law) and its Executive Regulations. Covers data controller and processor obligations, data subject rights, cross-border transfer requirements, sensitive data processing, and UAE Data Office enforcement. Keywords: UAE PDP, Federal Decree-Law 45, UAE Data Office, DIFC, ADGM, cross-border transfer.

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。

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.

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。

Guides DPIA for marketing profiling, behavioural targeting, cross-device tracking, and advertising analytics. Covers ePrivacy Directive Art. 5(3) cookie consent, PECR regulations, legitimate interest balancing for direct marketing, and adtech processing chain assessment. Keywords: marketing analytics, DPIA, profiling, behavioural targeting, cross-device tracking, ePrivacy, PECR, adtech, legitimate interest.

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。

Applies the reasoning, principles, and frameworks of Andrew Ng (machine learning pioneer, co-founder of Coursera and DeepLearning.AI, Stanford University, and former Google Brain lead). Use this skill whenever the user is navigating AI application development, agentic workflows, automation strategy, AI-native software engineering, or rapid prototyping. Trigger this skill when discussing career advice in the AI era, evaluating AI regulations, structuring machine learning projects, or deciding how to integrate AI into a business. It emphasizes task-based automation, data-centric ML, and driving the cost of proof-of-concepts to zero.

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。

Navigate privacy regulations (GDPR, CCPA), review DPAs, and handle data subject requests. Use when reviewing data processing agreements, responding to data subject access or deletion requests, assessing cross-border data transfer requirements, or evaluating privacy compliance.

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。

Test application security against OWASP Top 10 (2025) with automated CI tooling: OWASP ZAP (DAST), dependency/supply-chain scanning (OSV-Scanner, SBOM, provenance), Semgrep SAST, auth/session tests (JWT, OAuth, RBAC), and XSS/CSRF/SQLi/SSRF Playwright patterns. Use when: "security test," "OWASP," "vulnerability," "ZAP," "XSS," "SSRF," "dependency scan," "auth testing," "OWASP LLM Top 10." Scope is automated scanning + negative-path security tests in CI, not manual penetration testing. Not for: mapping security controls to regulations (SOC 2, HIPAA, PCI, GDPR) — use compliance-testing; pipeline stage wiring and deploy gating mechanics — use ci-cd-integration; purely functional API auth/input tests with no attacker model — see api-testing; testing your product's own LLM features or defending the agent itself (prompt-injection detector, indirect injection, jailbreak red-teaming) — use ai-system-testing. Related: ci-cd-integration, compliance-testing, api-testing, shift-left-testing, ai-system-testing.

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 implementing ITAR/EAR compliance, ECCN classification, party screening, technology control plans, or deemed exports - covers US export control regulationsUse when ", " mentioned.

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。

Audit web pages and components for WCAG 2.2 accessibility compliance. Use when a user asks to check accessibility, find a11y issues, audit for WCAG compliance, fix screen reader problems, check color contrast, ensure keyboard navigation works, or prepare for accessibility regulations like the European Accessibility Act or ADA.

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。

Applies the reasoning, principles, and frameworks of Andrew Ng (machine learning pioneer, co-founder of Coursera and DeepLearning.AI, Stanford University, and former Google Brain lead). Use this skill whenever the user is navigating AI application development, agentic workflows, automation strategy, AI-native software engineering, or rapid prototyping. Trigger this skill when discussing career advice in the AI era, evaluating AI regulations, structuring machine learning projects, or deciding how to integrate AI into a business. It emphasizes task-based automation, data-centric ML, and driving the cost of proof-of-concepts to zero.

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。

用于查询、检索、核验、下载、导出、批量采集中国官方法律法规、规章、条约和具体法条。Use this skill aggressively when the user asks to 查法律、查法规、查条例、查规章、查条约、查法条、查第几条、找法律依据、引用法律依据、核验现行有效、判断是否废止/已修改/尚未生效、下载法规全文、导出法规目录、批量下载法规文件、按关键词检索具体法条、展开法条分析，或在中国法律咨询、案例分析、合规审查、合同审查、劳动争议、行政法分析、公司合规、数据合规、政策研究中需要调用、核验或引用中国现行有效法律法规原文作为依据。Trigger also when phrases such as 依法、依规、依照法律规定、法律法规 imply a need to verify specific statutory authority or article-level text. Covers 国家法律法规数据库 (flk.npc.gov.cn), 国家规章库 (gov.cn), 外交条约库 (treaty.mfa.gov.cn), 国务院政策文件库 (sousuo.www.gov.cn), 司法部行政法规库 (xzfg.moj.gov.cn), 党内法规库 (12371.cn), 国防部法规文库 (mod.gov.cn), 税务法规库 (fgk.chinatax.gov.cn), 生态环境部法规规章 (mee.gov.cn), and 最高人民法院发布栏目 (court.gov.cn). Supports 标题/正文检索, 精确/模糊检索, 时效性过滤, 分类过滤, 分页, 排序, 单篇下载, 批量下载, 法条级抽取, 地区/制定机关分类, and browser fallback. Trigger when the answer may depend on current effective Chinese statutes, regulations, rules, treaties, article text, official document status, or official source attribution. Do not use for purely general legal theory, generic writing, or legal reasoning that does not require retrieving or verifying official Chinese legal documents.

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。

Expert in used vehicle sales business - market dynamics, pricing strategies, financing, insurance, dealer operations, customer acquisition, inventory management, and automotive industry regulations in Mexico

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 identifying cybersecurity-specific regulations and incident reporting obligations. Covers NIS2, DORA, SEC cyber disclosure rules, CISA incident reporting, state breach notification laws, cyber insurance requirements, and security certification frameworks. USE FOR: NIS2, DORA, SEC cybersecurity rules, CISA, breach notification, incident reporting, SOC 2, ISO 27001, cyber insurance, FedRAMP, StateRAMP, CMMC, data breach response DO NOT USE FOR: implementing security controls (use security skills), security testing tools (use security/security-testing), general data privacy (use privacy-data-protection)

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。

This skill enables Claude to automatically check for HIPAA (Health Insurance Portability and Accountability Act) compliance issues in codebases, infrastructure configurations, and documentation. It leverages the hipaa-compliance-checker plugin to identify potential violations related to data privacy, security, and access controls. Use this skill when the user explicitly requests to "check HIPAA compliance", "scan for HIPAA violations", "assess HIPAA readiness", or similar phrases related to HIPAA audits and security best practices. It is useful for projects handling protected health information (PHI) and requiring adherence to HIPAA regulations.

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。