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概要と使いどころ
Architect Unity 6.3 LTS data and decoupling with ScriptableObjects: config/data assets, shared runtime variables, event channels, and runtime sets/registries. Use when designing data-driven systems, replacing singletons/managers, creating .asset data with CreateAssetMenu, or when the user mentions ScriptableObject, SO architecture, or data assets.
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。
Get foreign qualifications, degrees, or professional licenses recognised in a new country — figure out whether recognition is even needed, which body assesses it, what evidence they want, and the bridging route if there's a gap. Use when someone says 'get my degree recognised abroad', 'is my foreign license valid here', 'credential evaluation', or 'can I work as a [nurse/engineer/teacher] in [country] with my qualifications'. Produces a recognition roadmap, the assessing body, an evidence checklist, and the bridging options. Routes to official assessment bodies; requirements are country- and profession-specific.
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。
Show or change the Cassette editing model and thinking level for the current media session. Invoke only when the user explicitly asks for the model picker, wants to inspect the current Cassette model, or requests a model/thinking change.
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。
Assemble a myth-vs-fact kinetic-typography explainer video ad (≈29.5s, 9:16) from N myth/fact pairs + hook / turn / punch copy + palette + a brand end-card PNG + a VO track — a hook, 3 red-strike MYTH cards that flip to teal-check FACT cards (per-line strikethrough that crosses EVERY wrapped line), a "what actually works" turn, an optional proof reveal, a punch line, and a static end card. DETERMINISTIC assembly with ZERO AI-gen visuals — HTML hyperframes rendered frame-exact via Playwright (`window.renderAt(t)`, animation a pure function of beat-local time), Whisper beat-snap to VO word onsets, concat at a uniform fps, karaoke `.ass` captions burned last (suppressed on the proof + end-card beats), and a VO + optional music mix (music −20 dB, `amix normalize=0`, tail fade). FREE (Python + Playwright + ffmpeg); the recipe supplies the copy / palette / end-card / VO and gates the paid VO / music / Whisper calls to their own capabilities. Use for the myth-vs-fact format.
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。
Profiles a genome from raw reads BEFORE assembly with a k-mer spectrum (KMC or Jellyfish histogram), then models it with GenomeScope2 to estimate genome size, heterozygosity, repeat content, and ploidy, and Smudgeplot to infer ploidy from heterozygous k-mer pairs (diploid AB vs triploid AAB vs tetraploid AABB). Covers choosing k via Merqury best_k.sh, the k-mer-coverage vs sequencing-coverage confusion, reading het/repeat/contamination/organelle peaks, why noisy ONT must not be used for counting, and how the estimate becomes the NG50 denominator, the Flye -g value, the hifiasm --hom-cov/purge setting, and the 1.5-2x-too-big haplotig sanity check. Use when starting any de novo assembly, deciding whether short reads can work, estimating genome size for an unknown organism, diagnosing ploidy, or sanity-checking an assembly's size against expectation.
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。
Find and query PI assets using MATLAB's Industrial Communication Toolbox. Two paths: (1) direct PI tag lookup via piclient + tags when user provides a tag name or description (R2022a+), (2) Asset Framework navigation via afclient when user needs element/attribute hierarchy (R2026a+). Use when working with PI AF servers, PI Data Archive tags, asset hierarchies, element templates, attribute lookup, or historical data from OSIsoft PI 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。
EU NIS2 Directive (Directive (EU) 2022/2555) compliance advisor for essential and important entities: entity classification, Art. 21 risk management measures, Art. 23 incident reporting timelines (24h/72h/1 month), Art. 20 governance obligations, supply chain security (Art. 21(2)(d); coordinated risk assessments Art. 22), gap assessments, policy drafting, ISO 27001 alignment, and penalty exposure analysis. Also covers Commission Implementing Regulation (EU) 2024/2690, the technical/methodological sub-requirements for Art. 21(2) and the significant-incident thresholds binding on DNS/cloud/data-centre/MSP/MSSP/trust-service and other digital entities. Use for NIS2 readiness, transposition questions, ENISA technical implementation guidance, significant-incident thresholds, supervisory differences between essential and important entities, and cross-border coordination.
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 quizzes, personality assessments, and recommendation tools that segment users into actionable categories rather than generating clicks for clicks' sake. Question architecture, scoring algorithms, result categorization, recommendation mapping, lead capture integration. Honest about clickbait-quiz (engagement only), vanity-result (entertaining, not useful), and actionable-segmentation (genuine categorization that drives next-step recommendations) patterns. Triggers on quiz, assessment, personality test, recommendation tool, scorecard, diagnostic, fit evaluator, what-type-of-X-are-you, persona quiz. Also triggers when an audience needs a categorization-driven lead magnet, when a vanity quiz is producing engagement but no qualified leads, or when an assessment is being scoped for the first 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。
Integrates Amazon Location Service APIs for AWS applications. Use this skill when users want to add maps (interactive MapLibre or static images); geocode addresses to coordinates or reverse geocode coordinates to addresses; calculate routes, travel times, or service areas; find places and businesses through text search, nearby search, or autocomplete suggestions; retrieve detailed place information including hours, contacts, and addresses; monitor geographical boundaries with geofences; or track device locations. Covers authentication, SDK integration, and all Amazon Location Service capabilities.
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。
Risk-based vendor assessment framework for IT service providers, technology vendors, and third-party partners under DORA, NIS2, GDPR. Provides three-phase process (Initial Screening / Detailed Assessment / Final Evaluation), six-dimension risk scoring (Financial/Operational/Compliance/Security/Reputational/Strategic) with weighted matrices, full DORA Art. 28-30 contractual checklist, NIS2 Art. 21(2) security measures enumeration, GDPR Art. 28 documentation checks, red flags per dimension, trigger-based review criteria, and document templates. Use when: (1) Evaluating new vendors or technology providers, (2) Conducting critical ICT third-party due diligence under DORA, (3) Performing supply chain security assessment under NIS2, (4) Creating vendor onboarding documentation, (5) Establishing ongoing vendor monitoring, (6) Assessing concentration risk, or (7) Generating executive vendor risk reports.
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。
GDPR Transfer Impact Assessment for Chapter V transfers under the EDPB Recommendations 01/2020 six-step methodology, the CNIL TIA Guide (January 2025), and EDPB essential guarantees. Handles transfer qualification, Art. 45 adequacy fast-tracks, Art. 46 full assessments with country profiles for 12 jurisdictions, and balanced Art. 49 derogation analysis. Outputs a Markdown report, a .docx formal TIA, and a JSON delta for RoPA interchange.
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。
EU NIS2 Directive (Directive (EU) 2022/2555) compliance advisor for essential and important entities: entity classification, Art. 21 risk management measures, Art. 23 incident reporting timelines (24h/72h/1 month), Art. 20 governance obligations, supply chain security (Art. 21(2)(d); coordinated risk assessments Art. 22), gap assessments, policy drafting, ISO 27001 alignment, and penalty exposure analysis. Also covers Commission Implementing Regulation (EU) 2024/2690, the technical/methodological sub-requirements for Art. 21(2) and the significant-incident thresholds binding on DNS/cloud/data-centre/MSP/MSSP/trust-service and other digital entities. Use for NIS2 readiness, transposition questions, ENISA technical implementation guidance, significant-incident thresholds, supervisory differences between essential and important entities, and cross-border coordination.
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。
Assess whether Government of India approval is required for foreign investment in an Indian company under Foreign Exchange Management Act, 1999 and the Non-Debt Instruments Rules, 2019. The skill systematically gathers transaction details, evaluates sectoral entry routes and caps, assesses land border country restrictions under applicable laws, and delivers a preliminary compliance note. Produces clear guidance on whether the investment falls within Automatic Route or requires Government approval.
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 a high-fidelity interactive legal assessment as a single self-contained HTML artifact. Output includes a live countdown timer, contract review tasks with hover-annotated problem clauses, candidate answer textareas, model answers hidden behind reveal blocks, scenario-based legal memo tasks, strategy and function-building questions, and a pre-submission checklist that encodes the marking criteria. Use when the user needs to (1) assess a legal candidate with a realistic timed exercise, (2) train or onboard junior lawyers using problem sets rather than doctrine, (3) help a candidate prepare for a real take-home assessment they are facing, (4) build educational materials for law students, in-house teams, or compliance training, or (5) produce scenario-based training modules on specific legal topics. Triggers on "legal test", "take-home", "mock exam", "contract redline exercise", "candidate assessment", "legal training exercise", "practice test", or similar phrasing even when informal.
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。
Assess whether a Fundamental Rights Impact Assessment (FRIA) is required under Article 27 EU AI Act, and structure or draft that assessment for a specific high-risk AI deployment. Covers deployer scope gating (public bodies and private entities providing public services), affected group mapping, Charter rights analysis, proportionality, safeguards evaluation, residual risk, DPIA/FRIA cross-referencing under the amended Article 27(4), the unconditional notification duty under Article 27(3), and DACH-specific considerations. Use when asked about FRIA obligations, Article 27 scope, fundamental rights and AI, or deployer assessment duties.
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。
Assess and operationalize implementation readiness for high-risk AI systems under the EU AI Act Annex III, including provider and deployer obligations, conformity assessment, post-market monitoring, and EU database registration. Use when users say things like “we classified this as high-risk, what now?”, “build an EU AI Act readiness plan”, “assess our Annex III compliance gaps”, “what do providers/deployers of high-risk AI need to implement?”, “prepare for conformity assessment”, or “create a high-risk AI implementation roadmap.”
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。
Fast 15-25 minute triage for preliminary EU AI Act classification and compliance assessment. This skill should be used when the user asks to "do a quick AI Act assessment", "check if the AI Act applies to us", "run a preliminary classification", "do an AI Act triage", "quick check", "preliminary assessment", "Schnellprüfung", "Ersteinschätzung", or needs a fast initial assessment before committing to full 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。
Design a single-point rubric with one criterion and open columns for evidence. Use for student self-assessment, peer feedback, teacher formative feedback, or pre-task planning. Works with any learning target, with or without a band system.
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。
Design multi-informant assessment approaches for dispositional competencies like curiosity or resilience. Use when assessing character strengths or competencies that written tests cannot capture.
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 a proposed assessment for construct validity, reliability, and alignment to learning objectives. Use when reviewing or quality-assuring assessments before deployment.
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 a test file or suite; produce a severity-ranked diagnostic report. ALWAYS USE for tests that verify nothing, missing/tautological assertions, swallowed/broad exceptions, flaky/order-dependent tests, duplication, or magic values. Polyglot. DO NOT USE for direct edits: writing-mstest-tests owns supplied MSTest assertions/attributes/lifecycle; code-testing owns new tests. Exclude running tests, migration, assertion metrics (assertion-quality), raw .NET coverage collection (run-tests), non-.NET coverage collection/analysis (native tooling), project-wide .NET coverage/CRAP (coverage-analysis), named-target .NET CRAP (crap-score), behavioral/pseudo-mutation gaps (test-gap-analysis), test-mix/ happy-vs-error classification and trait distributions (test-tagging), or the testsmells.org catalog (test-smell-detection).
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。
Binary analysis, assembly interpretation, disassembly, decompilation, firmware RE, and protocol reverse engineering
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 post-Schrems II Transfer Impact Assessment process following EDPB Recommendations 01/2020 six-step methodology. Covers assessment of third country legal frameworks, supplementary measures evaluation, and TIA scoring. Activate for international data transfers, SCCs, third-country adequacy, or Chapter V compliance. Keywords: TIA, Schrems II, transfer assessment, EDPB, supplementary measures, SCCs, international 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 retention impact assessments for new processing activities to determine appropriate data retention periods. Covers regulatory requirements scanning, proportionality review, purpose-based retention determination, and retention period documentation aligned with GDPR Article 5(1)(e) and Article 25 data protection by design. Activate for retention assessment, new processing retention, retention period determination 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。