977 件 ・ 関連度順
概要と使いどころ
Implements GDPR Art. 22 automated decision-making and AI Act Art. 14 human oversight requirements for AI systems. Covers identification of solely automated decisions, meaningful human intervention design, logic explanation mechanisms, and contestation procedures. Keywords: Art. 22, automated decision, human oversight, AI Act, profiling, contestation.
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 GDPR Article 22 rights related to solely automated decision-making and profiling, including identification of automated decisions, meaningful human oversight implementation, logic explanation requirements, and contestation mechanisms. Activate for automated decision, profiling, Art. 22, algorithmic decision, AI decision 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。
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.
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。
X (Twitter) DM automated chat end-to-end Skill: scan DM inbox to identify pending-reply conversations, read message history, generate persona-based replies and send; also supports searching users and starting new conversations. Built-in E2E passcode unlock, DM permission filtering, and rate control. Use when user mentions X auto-reply DMs, Twitter DM automated chat, auto-handle unread DMs, reply to X private messages with persona, X DM outreach campaign, batch send DMs to Twitter users, auto-process pending DM replies, Twitter DM bot, automated Twitter outreach, X direct message automation.
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。
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。
Managing privacy risks from AI-driven inferences about individuals including derived data classification, profiling under GDPR Art. 22, inference accuracy obligations, and controlling automated personality/behaviour predictions. Keywords: AI inference, derived data, profiling, automated predictions, GDPR.
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 automated data deletion workflows for GDPR Article 17 right to erasure and retention period expiry. Covers cascading deletion across dependent systems, dependency handling for referential integrity, confirmation logging, and audit trail generation. Activate for automated deletion, erasure automation, data purge, retention expiry 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。
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 compliance with Australia's Privacy Act 1988 including the 2024 reform amendments. Covers automated decision-making transparency, children's privacy code, individual rights expansion, enforcement strengthening, and the Australian Privacy Principles (APPs). Keywords: Australia Privacy Act, APPs, OAIC, automated decisions, children privacy code, privacy reform.
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 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.
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 AI transparency requirements under EU AI Act Arts. 13-14 and GDPR Arts. 13-14. Covers user notification of AI interaction, system capability disclosure, limitation documentation, and meaningful information about automated logic. Keywords: AI transparency, EU AI Act, GDPR notification, explainability, 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。
Automated API testing with Postman collections via Newman CLI. Use when user requests API testing, collection execution, automated testing, CI/CD integration, or mentions "Postman", "Newman", "API tests", "run collection", or "automated 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。
macOS上のOpenClawをmainの最新版へ更新し、Gatewayとアプリの動作を確認します。CIの失敗修正や、公開を伴わないリリース検証も扱います。
GitHubのIssueやPRを確認・作成し、コメントやレビュー、CIの実行結果を扱います。失敗ログの調査や再実行、承認されたマージの状態確認にも対応します。
コーディングの作業ログを振り返り、ファイルの探しやすさ、自動チェック、指示文、ツール利用などを点検して、次回に向けた環境改善案を重要度順に整理するスキル。
コミット直前に変更ファイルを整形し、既存の型チェックとテストを実行する仕組みを設定します。Huskyとlint-stagedの導入から設定・動作確認まで扱うスキルです。
Webアプリの本番公開に向けて、Docker構成やテスト・公開の自動化を整え、更新方式の選定から稼働確認、障害時の復旧手順まで支援するスキル。
Webアプリの本番公開に向け、CI/CDによるテストと配布の自動化、Docker化、稼働確認、切り戻し手順、公開前の確認項目を整理するスキル。
When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," "lifecycle emails," "trigger-based emails," "email funnel," "email workflow," "what emails should I send," "welcome series," or "email cadence." Use this for any multi-email automated flow. Emails avoid AI tells like 'it's not X, it's Y' reveals, 'no X, no Y, no Z' lists, and fake 'Re:' subject lines. For cold outreach and outbound sequences, see cold-email. For in-app onboarding, see onboarding.
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。
Add end-to-end and API tests for features that already work, following the project's existing test harness. Use when the user asks for e2e tests, API tests, or automated coverage of an existing feature, or says "create qa automated tests for [feature]". Not for unit tests on work in flight, which the build writes.
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。
Triage Monte Carlo alerts interactively or build an automated workflow. Fetch, score, and troubleshoot alerts using MCP tools now, or design a reusable workflow that runs on a schedule.
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 and operationalize Amazon GuardDuty, covering protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity, and building automated response with EventBridge and Lambda. Use when establishing threat detection for AWS accounts, investigating findings on compromised instances or credential abuse, or building automated incident-response playbooks.
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。
Build automated AWS GuardDuty finding response pipelines using EventBridge and Lambda to trigger real-time incident response, automatically quarantine compromised resources, and route security notifications. Use when designing automated remediation playbooks for GuardDuty findings across VPC Flow Logs, CloudTrail, DNS, EKS, or S3 data events, or when reducing mean time to respond to cloud threats.
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。