「rds」の検索結果

Defines testing quality metrics, coverage thresholds, and anti-patterns. Use when establishing test gates or validating a test suite's coverage targets.

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 UK Age Appropriate Design Code (Children's Code) 15 standards under the Data Protection Act 2018 Section 123. Covers best interests assessment, age-appropriate application, transparency, data minimization, geolocation restrictions, and profiling defaults. Keywords: AADC, Children's Code, ICO, age appropriate design, UK.

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 privacy program effectiveness measurement including leading and lagging indicators, KPI definition, benchmarking methodology, executive reporting formats, board-level privacy dashboards, and metric-driven program improvement. Covers operational, compliance, risk, and strategic privacy metrics across the program lifecycle. Keywords: privacy metrics, KPIs, benchmarking, executive reporting, dashboard, program effectiveness.

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 compliance with South Korea's Personal Information Protection Act (PIPA, 개인정보 보호법). Covers pseudonymisation framework, notification requirements, PIPC enforcement, consent standards, and cross-border transfer rules under the 2023 amendments. Keywords: PIPA, Korea data protection, PIPC, pseudonymisation, consent, cross-border transfers.

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 health and medical data processing covering Art. 9(2)(h)-(j) exemptions, HIPAA crosswalk for transatlantic operations, clinical trial data protection under EU CTR 536/2014, and genetic data specifics under Art. 9(1). Activate for healthcare systems, clinical research, health apps, or medical device data. Keywords: health data, DPIA, Art. 9, clinical trial, genetic data, HIPAA, medical records, special category.

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。

Addresses HIPAA privacy and security requirements for health data interoperability under the 21st Century Cures Act, ONC Health IT Certification Program, and CMS Interoperability and Patient Access Final Rule. Covers information blocking prohibitions, FHIR API patient access, TEFCA exchange purposes, and privacy safeguards for health information exchange. Keywords: interoperability, information blocking, FHIR, TEFCA, Cures Act, patient access API, health information exchange.

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 RoPA for complex multi-entity corporate groups including entity-level versus group-level records, intra-group transfer documentation, and shared processing coordination. Activate for group RoPA, multi-entity, corporate group, intra-group transfers, subsidiary records, holding company.

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 implementation of the GDPR accountability principle under Articles 5(2) and 24, including documentation requirements for policies, DPIAs, RoPA, training records, and breach logs. Activate when establishing or reviewing accountability measures, preparing evidence portfolios, or demonstrating compliance to supervisory authorities. Keywords: accountability, Article 5(2), Article 24, documentation, compliance evidence, governance.

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 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.

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。

Builds comprehensive data inventory per GDPR Art. 30 Records of Processing Activities. Covers system-by-system discovery, data flow diagramming, third-party identification, and legal basis per category. Keywords: data inventory, data mapping, Art 30, RoPA, data flow, processing activities.

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 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.

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。

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, transfer exceptions, explicit consent, compelling legitimate interests.

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。

Provision and manage RDS databases. Configure backups, replication, and security. Use when deploying managed relational databases on AWS.

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 patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions.

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This skill should be used when the user asks to "create a style sheet", "style guide", "house style", "keep the voice consistent", "voice drift", "British or American spelling", "character voices", "lint the prose", "prose check", "filter words", "said-bookisms", "overused words", "repeated phrases", "similar character names", "voice fingerprints", or wants to record and enforce the voice and surface conventions of a story project. NOT for rewriting dialogue to make the voices distinct when everyone sounds the same (use line-editing), or a character's profile or arc (use character-management).

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。

Creates and maintains project documentation for features, systems, and components. Use when documenting how a feature, system, or component works — including writing, updating, or organizing docs. Does not scan or detect the project's technology stack — use project-discovery for repository analysis and config detection. Does not create architectural decision records — use architectural-decision-record for ADRs. Does not create or update coding standards — use coding-standard instead. Does not generate PR descriptions — use update-pr-description for that. Does not produce runbooks for operational scenarios — use runbook for that. Does not rewrite existing prose for readability — use edit-for-readability for that. Does not produce an ephemeral, understand-now overview of code or a PR — use code-overview for that.

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。

Creates or updates project documentation for a feature, system, or component and publishes it to a user-specified Confluence location. Use when the user wants feature or system documentation written to Confluence, posted to a Confluence space or page, or synced to a Confluence location. Requires a configured Atlassian MCP server. Does not document to local files only — use project-documentation for that. Does not publish an arbitrary existing markdown file — use markdown-to-confluence for that. Does not plan or specify a new feature to Confluence — use plan-a-feature-to-confluence for that. Does not create architectural decision records — use architectural-decision-record. Does not create coding standards — use coding-standard. Does not produce runbooks — use runbook.

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 market environment analysis and reporting tool. Analyzes global markets including US, European, Asian markets, forex, commodities, and economic indicators. Provides risk-on/risk-off assessment, sector analysis, and technical indicator interpretation. Triggers on keywords like market analysis, market environment, global markets, trading environment, market conditions, investment climate, market sentiment, forex analysis, stock market analysis, 相場環境, 市場分析, マーケット状況, 投資環境.

Fix SQLite "database disk image is malformed" errors caused by corrupted FTS5 indexes. Use when: (1) UPDATE/INSERT fails with "stepping, database disk image is malformed" but PRAGMA integrity_check returns "ok", (2) Only specific records fail to update while others succeed, (3) Records contain dirty text with tabs, newlines, or unusual characters that were inserted into FTS5-indexed columns. The misleading error message suggests disk corruption, but the actual issue is FTS5 index corruption from malformed text content.

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。

Debug "API returns data that doesn't exist in database" when multiple Kubernetes clusters exist (production, staging, POC). Use when: (1) REST API returns records that direct database queries can't find, (2) Data counts match approximately but specific records don't overlap, (3) kubectl context points to a different cluster than the one serving the public domain, (4) ClickHouse/Postgres queries return stale or different data than the API, (5) "completely different datasets" despite same table names and schemas. Root cause: querying the wrong cluster's database.

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。

Fix incorrect priority ordering when using denormalized aggregate columns. Use when: (1) Records are processed in wrong order despite ORDER BY on count/sum columns, (2) Top items by some metric aren't being selected first, (3) Aggregate columns show 0 or NULL for records that should have high values, (4) Priority queue processes low-value items before high-value ones. The root cause is often that denormalized columns (vine_count, loop_count, total_orders, etc.) weren't backfilled or maintained properly. Solution: JOIN with source tables to compute actual aggregates at query time.

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。