クラウド、CI/CD、監視、デプロイ（6,720 件）
概要と使いどころ
Manages legal hold and data preservation processes including triggering events, custodian notification, hold-in-place technical implementation, release procedures, and interaction with retention schedules. Covers litigation hold registers, compliance monitoring, and Art. 17(3)(e) exception documentation. Activate for legal hold, litigation preservation, data freeze, e-discovery hold 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。
Deploy differential privacy in production systems including epsilon selection strategies, noise calibration with Laplace and Gaussian mechanisms, privacy budget tracking, composition theorems, and Python implementation patterns. Covers both central and local differential privacy models.
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 Data Protection Impact Assessments for employee monitoring systems per EDPB Guidelines 3/2019 on workplace data processing. Covers video surveillance, email monitoring, GPS tracking, keystroke logging, and productivity tools. Applies proportionality testing under Art. 35 GDPR. Keywords: DPIA, employee monitoring, surveillance, proportionality, EDPB, workplace privacy, keystroke logging, GPS tracking.
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。
Manages Data Subject Access Request procedures for employee requests under Art. 15 GDPR. Covers scope of disclosable HR records, emails, CCTV footage, performance reviews, monitoring data, and training records. Implements third-party data redaction, legal professional privilege, exemptions for ongoing proceedings, and the one-month response timeline. Keywords: DSAR, subject access request, Art. 15, employee records, redaction, privilege, HR data, SAR.
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 workplace monitoring including email surveillance, internet usage monitoring, CCTV, GPS tracking, and keystroke logging. Covers GDPR Art. 88 employment context provisions, WP29 Opinion 2/2017 on data processing at work, and proportionality balancing for employee monitoring. Keywords: employee surveillance, workplace monitoring, DPIA, Art. 88, WP29 Opinion 2/2017, CCTV, email monitoring, GPS tracking.
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。
Configures cloud storage retention policies across AWS S3, Azure Blob Storage, and Google Cloud Storage. Covers lifecycle rules, object lock, legal hold, immutability policies, cross-region replication retention alignment, and compliance mode configuration. Activate for cloud retention, S3 lifecycle, Azure retention, GCP retention policy 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。
Guides managing conflicting privacy requirements across jurisdictions. Covers data localisation vs transfer freedom, consent standards variation, age thresholds, breach timelines, and resolution frameworks for incompatible obligations. Keywords: conflicting laws, data localisation, consent variation, age thresholds, resolution framework.
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 the end-to-end GDPR Data Protection Impact Assessment process under Article 35, including mandatory trigger identification per Art. 35(3), DPIA content requirements per Art. 35(7), and EDPB WP248rev.01 methodology. Activate for systematic profiling, large-scale special category processing, or large-scale public monitoring. Keywords: DPIA, Article 35, impact assessment, WP248, data protection, risk assessment.
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。
Cloud service provider privacy assessment framework. Covers ISO 27018 cloud privacy controls, CSA STAR certification, SOC 2 Type II evaluation, shared responsibility model mapping, data residency verification, and cloud-specific privacy risk analysis.
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 migrating personal data to cloud infrastructure covering controller-processor analysis under Art. 28, international transfer assessment, encryption requirements, and shared responsibility model evaluation. Activate for cloud adoption, SaaS procurement, or data centre migration projects. Keywords: cloud migration, DPIA, Art. 28, processor, encryption, shared responsibility, SaaS, IaaS, PaaS.
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 BYOD privacy compliance frameworks for personal device use in the workplace. Covers personal vs corporate data separation, MDM capabilities and limitations, employee consent requirements, data wiping boundaries, and monitoring restrictions on personal devices. Keywords: BYOD, mobile device management, MDM, personal device, data separation, containerisation, remote wipe, employee privacy.
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。
Generates Records of Processing Activities automatically from IT system inventories including Active Directory, cloud service catalogs, API gateway logs, and database schemas. Covers automated field population, data flow discovery, and system-to-RoPA mapping. Activate for automated RoPA, system inventory, data discovery, auto-population, IT-driven records.
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 structured post-breach remediation using a lessons learned framework covering root cause remediation, control gap closure, policy updates, training modifications, monitoring enhancements, and regulatory follow-up. Provides a systematic approach to preventing breach recurrence and demonstrating accountability to supervisory authorities. Keywords: post-breach, remediation, lessons learned, root cause, control gap, policy update, training.
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。
Manages coordinated breach notification across multiple legal jurisdictions including EU member states (72-hour GDPR deadline), US state breach notification laws (varying timelines from 30 to 90 days), and other international regimes. Covers conflict resolution when notification timelines differ, lead supervisory authority determination, and parallel notification execution. Keywords: multi-jurisdiction, cross-border breach, notification coordination, GDPR, US state laws, international breach notification.
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 technical breach detection capabilities including SIEM integration, DLP alert configuration, anomaly detection rules, and insider threat monitoring. Provides a breach classification taxonomy across confidentiality, integrity, and availability dimensions. Covers detection tool selection, alert tuning, and integration with privacy incident response workflows. Keywords: breach detection, SIEM, DLP, anomaly detection, insider threat, classification.
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。
Coordinates credit monitoring and identity theft protection services for individuals affected by a data breach. Covers vendor selection criteria, enrollment logistics, coverage duration (12-24 months), identity theft insurance options, communication to affected individuals, and enrollment rate tracking. Keywords: credit monitoring, identity protection, breach response, Experian, enrollment, identity theft insurance.
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。
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.
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 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.
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 the user needs engineering or research-paper figures: system architecture diagrams, algorithm workflows, hardware schematics, benchmark charts, ablation plots, figure briefs, redraws, image edits, or exact publication-style plots from numeric data. Covers Gemini, Nano Banana, OpenAI image models, and local plotting 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。
Analyzes an existing codebase using strategic Domain-Driven Design to discover bounded contexts, surface ubiquitous language and semantic collisions, find places where code boundaries diverge from domain boundaries, and produce an evidence-backed domain and context map. Use when the goal is DDD-specific: bounded context discovery, ubiquitous language analysis, domain model discovery, or mapping contested ownership and responsibility. The entire repository is a valid scope; no module or directory must be named first. Does not assess architectural coupling, cohesion, or technical debt — use architectural-analysis. Does not design service communication, integration patterns, or deployment topology — use architectural-analysis or plan-a-feature. Does not refactor code, diagnose bugs, or review code quality — use refactor, investigate, or code-review.
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。
Plan and verify software releases with versioning, changelogs, release branches, feature flags, canaries, migration gates, rollback, deployment checks, and release readiness. Use when preparing a release, shipping a risky PR, coordinating app/backend/database rollout, recovering from a bad deploy, or defining release policy for a repo.
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。
Observability and SRE expert. Use when setting up monitoring, logging, tracing, defining SLOs, or managing incidents. Covers Prometheus, Grafana, OpenTelemetry, and incident response best practices.
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。
在已经过独立验证的 CLIProxyAPI upstream 之上部署 NewAPI 计费层，把 Codex/Claude/Gemini/Qwen 等订阅账号包装成可计费的 OpenAI 兼容 API。本 Skill 不负责新建裸 CLIProxyAPI；负责 NewAPI Docker 部署、容器到宿主桥接、模型计费倍率、参数化额度修正、多账号 OAuth 凭据热加载和双路径验证。当用户说“给现有 cliproxy 加 NewAPI”“配置 NewAPI 渠道接已运行的 cliproxy”“NewAPI 价格不对”“给现有部署加账号”“172.17.0.1 容器网络”或“408 冷却放大故障”时触发。
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。
在本机 Mac 或 Apple Silicon 上部署 Gemma 4 12B。本地安装/升级 llama.cpp，下载 GGUF 量化模型，用 llama-server 暴露 OpenAI-compatible API，或用 Ollama 暴露本地模型服务；按用户需求在默认 Q4_K_M、64K/128K 长上下文、QAT Q4_0 @ 256K、左右对比演示之间选择，配置 tmux 后台运行，验证健康检查、问答接口、资源占用和常见故障。当用户说部署 Gemma 4、Gemma 4 12B、本地大模型、长上下文、QAT、量化、llama-server、Ollama、GGUF、Mac 本地模型服务时使用。
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。