「assess」の検索結果

Assess physical and transition climate risk for a site, product, or portfolio with scenario-based structure. Use when asked to run a climate risk assessment, evaluate physical or transition risk, prepare TCFD/ESRS-style climate risk analysis, or assess how climate scenarios affect an asset or business. Produces a hazard-exposure-vulnerability matrix across 2030/2040/2050 horizons and labelled scenarios, with financial-impact ranges, confidence levels, and adaptation options.

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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.

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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.

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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.

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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.”

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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.

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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 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。

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.

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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。

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.

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Conducts Privacy Impact Assessment for vendor and third-party data processing arrangements. Covers processor due diligence, Data Processing Agreement (DPA) requirements under GDPR Article 28, sub-processor management, cross-border vendor transfers, cloud service provider assessments, and ongoing vendor monitoring. Keywords: vendor PIA, processor assessment, DPA, Article 28, sub-processor, cloud privacy, third-party risk.

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Guides privacy program maturity assessment using the AICPA/CIPT Privacy Maturity Model with five levels: Ad Hoc, Repeating, Defined, Managed, and Optimized. Covers assessment methodology across ten privacy domains, scoring criteria, gap analysis, maturity roadmap generation, and benchmarking against industry peers. Keywords: privacy maturity, AICPA, maturity model, assessment, roadmap, benchmarking.

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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.

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Guides systematic assessment of current state versus GDPR requirements across all chapters with prioritised remediation matrix. Activate when starting compliance programmes or conducting periodic reassessment. Keywords: gap analysis, compliance assessment, remediation matrix, GDPR readiness.

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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.

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Conducts Data Protection Impact Assessments for AI and ML systems per EDPB Guidelines 04/2025 on AI processing. Covers training data lawfulness evaluation, model risk assessment, automated decision triggers, and AI-specific DPIA methodology. Keywords: AI DPIA, machine learning impact assessment, EDPB AI guidelines, model risk, training data.

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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。

Conduct Fundamental Rights Impact Assessments (FRIA) for high-risk AI systems as required by EU AI Act Article 27. Use when (1) deployers of high-risk AI systems (Annex III) need to assess fundamental rights impacts before first use, (2) public bodies or private entities providing public services are deploying AI systems, (3) credit scoring or insurance risk assessment AI systems are being deployed (Annex III 5b, 5c), (4) evaluating impact on natural persons' fundamental rights (dignity, liberty, privacy, data protection, non-discrimination, children's rights, etc.), or (5) creating EU AI Act Article 27 compliance documentation with market surveillance 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。

Design a compromise assessment — hunting scope, methodology, and evidence collection. Use when asked "are we compromised", "run a compromise assessment", or "scope a threat hunt".

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Assessing anthropogenic environmental impacts — pollution pathways, habitat destruction and fragmentation, land-use change, invasive species, overharvest, and extinction debt. Covers environmental impact assessment (EIA) methodology, exposure-effect relationships, population viability analysis, IPAT and ecological footprint frameworks, and strategic environmental assessment. Use when quantifying or forecasting human impacts on ecosystems, designing monitoring programs, or evaluating a proposed intervention against a baseline.

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。

Format and score completed plugin assessment findings without starting another assessment workflow. Use when a plugin assessment needs the standard report structure, scoring criteria, severity breakdown, or marketplace-readiness result.

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。