7,267 件 ・ 関連度順
概要と使いどころ
Implements telehealth privacy compliance covering HIPAA requirements for virtual care, state licensing and recording consent laws, platform security with BAA requirements for telehealth vendors, cross-state prescribing rules, and OCR enforcement discretion during public health emergencies. Keywords: telehealth privacy, virtual care, HIPAA, recording consent, platform BAA, cross-state licensing, OCR enforcement.
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。
Guides compliance with Thailand's Personal Data Protection Act B.E. 2562 (2019). Covers consent framework, DPO requirements, PDPC enforcement, lawful bases for processing, cross-border transfer mechanisms, and data subject rights under the PDPA. Keywords: Thailand PDPA, PDPC, consent, DPO, cross-border transfers, data subject rights.
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。
Links RoPA entries to Data Protection Impact Assessments and lawful basis assessments. Covers cross-reference systems, dependency tracking, and update cascade triggers between RoPA, DPIA register, and lawful basis documentation. Activate for RoPA-DPIA link, cross-reference, dependency tracking, impact assessment linkage, cascade updates.
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 Japan's Act on the Protection of Personal Information (APPI, 2022 amendments). Covers individual rights expansion, cross-border transfer restrictions including pre-transfer information requirements, PPC enforcement, and pseudonymised and anonymously processed information. Keywords: APPI, Japan data protection, PPC, cross-border transfer, pseudonymised information, individual rights.
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 compliance with country-specific data localization requirements across key jurisdictions including Russia (242-FZ), China (PIPL Art. 40, CAC measures), India (DPDP Act), Turkey, Vietnam, and Indonesia. Covers localization assessment, architecture design, and exemption procedures. Keywords: data localization, data residency, PIPL, 242-FZ, cross-border restrictions.
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 China's Personal Information Protection Law (PIPL, effective 1 November 2021). Covers consent requirements, cross-border transfer mechanisms (CAC security assessment, standard contracts, certification), separate consent triggers, and critical information infrastructure obligations. Keywords: PIPL, China data protection, CAC security assessment, cross-border transfer, separate consent, CIIO.
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。
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.
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 APEC Cross-Border Privacy Rules system certification process including self-assessment against the APEC Privacy Framework principles, accountability agent selection, intake questionnaire completion, certification decision, annual recertification, and Global CBPR Forum transition. Keywords: APEC, CBPR, cross-border privacy, accountability agent, certification, Global CBPR.
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。
Parallel multi-AI cross-validation research workflow (大版本). Dispatch N internal sub-agents + grok + gemini in parallel, automatically cross-validate findings, tier by confidence (strong consensus / partial / conflict / insufficient), generate tiered action items with arbitration. Use when user says "多 AI 调研", "交叉验证", "独立共识", "三脑调研", "multi-ai research", "parallel research", "cross-validate", or needs deep research that benefits from internal data + external 2026 consensus. NOT for quick factual Q&A, pure code reasoning, or tasks needing deep project context.
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 and safely repair cross-runtime Skill governance: canonical-source ownership, divergent or duplicate projections, exposure scopes and budgets, lifecycle drift, quarantine, and retirement. Use when the user explicitly requests cross-runtime or cross-scope Skill governance; ignore project-local Skill inventory, product/runtime loading or enablement checks, usage statistics, and mentions/traces.
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。
Track and analyze cross-border capital flows between mainland China and Hong Kong via Stock Connect (沪港通/深港通). Monitor northbound (北向资金) and southbound (南向资金) flows, identify trending stocks, and analyze institutional positioning. Use when user asks about 北向资金, 南向资金, 外资动向, Stock Connect flows, or cross-border investment trends.
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。
Adversarial verification of research theses — cross-run/cross-thesis contradiction via the entity index, pre-mortem (Klarman/Kahneman: assume the loss already happened, reverse the path), inversion (Munger: invert, always invert), and wrong_if falsifiability review. ≈50-finding cap sorted by severity; content-derived finding IDs; incremental scoping with three backstops; lifecycle hooks at pillar-complete / thesis-complete / pre-reduction.
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。
Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.
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。
Create cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill, audit this skill, is this skill safe, vet a skill before installing, what does this skill access. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, spec validation, and security auditing of third-party skills before install.
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。
Implement visual regression testing with Playwright screenshots, Chromatic, Percy, and Argos CI. Covers baseline management, diff threshold tuning, dynamic content masking, responsive viewport testing, and review/approval workflows. Use when: "visual test," "screenshot," "visual regression," "pixel diff," "snapshot diff," "update baselines," "Chromatic," "percy snapshot," "argos screenshot." Not for: bulk baseline regeneration after a redesign broke many tests — use selector-drift-recovery; cross-browser rendering matrices — use cross-browser-testing; general Playwright test structure — use playwright-automation. Related: playwright-automation, ci-cd-integration, cross-browser-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。
Analyze an open-source project from What/Why perspective (not how-it's-implemented). Use when the user says "/analyze-oss", "분석해줘 이 오픈소스", "이 레포 뭐하는거야", "analyze this repo", "what does X do", "이거 왜 쓰는거야", "이 라이브러리 분석", provides a GitHub URL and wants understanding, or asks to deeply understand an OSS project's purpose, value, target users, and usage flow. Clones the repo to ~/opensource-analysis/<repo-name>/ (git pull if already exists), dispatches parallel subagents per analysis lens, then synthesizes a What/Why-focused report in chat. Supports optional user-specific follow-up questions.
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。
Crossplane for infrastructure as code using Kubernetes CRDs. Use when the user needs to provision and manage cloud resources declaratively through Kubernetes APIs, compose custom infrastructure abstractions, or build internal platforms.
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。
Designing anatomically plausible, visually distinctive creatures that communicate threat, personality, and role through form - from terrifying bosses to collectible companionsUse when "creature design, design a creature, design a monster, monster design, boss design, enemy creature, companion creature, pet design, wildlife design, alien creature, fantasy creature, horror monster, cute creature, pokemon style, creature anatomy, creature silhouette, creature movement, hybrid animal, ecosystem creatures, creature family, mount design, dragon design, beast design, creature, monster, boss, enemy, companion, wildlife, horror, cute, pokemon, anatomy, silhouette, locomotion, ecosystem, hybrid, fantasy, sci-fi, kaiju, cryptid" 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。
Mastery of the new frontier: AI-generated video that rivals—and reimagines—traditional production. This skill covers Veo3, Runway Gen-3, Sora, Kling, Pika, Luma Dream Machine, and the rapidly evolving landscape of neural video synthesis. We're not just using AI to replace traditional video—we're unlocking visuals that were previously impossible, unaffordable, or unimaginable. Flying through abstract data visualizations, impossible camera moves, photorealistic product renders from text, and consistent character performances without actors or sets. The practitioners of this skill understand that AI video is not about cost savings— it's about creative expansion. The ceiling has been removed. What would you create if production cost was zero and physics was optional? Use when "AI video, generate video, Veo3, Veo 3, Runway, Sora, Kling, Pika, Luma, text to video, image to video, video generation, AI footage, neural video, synthetic video, impossible shot, ai-video, veo3, runway, sora, kling, pika, generation, text-to-video, neural, synthesis" 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。
Unified multi-platform paid media audit with parallel execution. Spawns scored audits for Google Ads, Meta Ads, and Microsoft Ads simultaneously, merges results into a budget-weighted aggregate health score (A-F), adds cross-platform analysis (budget allocation, tracking consistency, creative alignment, attribution overlap), and produces a prioritized action plan. Optionally generates a client-ready deck via pro-deck-builder. Use when the user asks for a full paid media audit, cross-platform review, or multi-channel ad 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。
Audit whether a paper's baseline comparisons are COMPLETE, FAIR, and SIGNIFICANT: a required recent SOTA baseline is missing while 'best/SOTA' is claimed (HP-MISSING-BASELINE); a baseline is undertuned / given less compute-tuning-data, run at a mismatched config, or the equal-budget ablation-as-baseline is absent (HP-WEAK-BASELINE); 'outperforms' is asserted over overlapping error bars or with no variance/seeds (HP-SIG-OVERLAP); and a cross-row 'improves over baseline by X%' is arithmetically wrong (HP-DELTA-ERROR, cross-row form only). A versioned per-domain baseline profile + a live leaderboard/recency search are assembled by the EXECUTOR as structured facts; a fresh cross-model reviewer (gpt-5.6-sol xhigh, read-only, fresh thread per dimension) PROPOSES findings, each span-anchored to a ledger claim_id; tools/adjudicate_findings.py DECIDES the verdict. Works at L0 (stated comparisons) and deepens at L2 (configs/result files). A completeness question it cannot settle internally becomes needs_external_check, never a guessed missing baseline. Emits baseline-comparison-audit.findings.json; computes NO verdict. Detect-only. Triggers: "baseline audit", "missing baselines", "is the comparison fair", "weak baseline", "baseline 误报", "SOTA earned?".
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。