「assessment」の検索結果

Analyse student work against criteria to identify specific gaps between current performance and learning objectives. Use when reviewing submissions, planning feedback, or diagnosing learning needs.

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Plan a unit using backwards design from desired outcomes through assessment evidence to learning activities. Use when starting a new unit or redesigning an existing one from standards.

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Design a checking-for-understanding protocol with specific techniques for each lesson stage. Use when planning systematic comprehension checks during explicit or direct instruction.

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Interpret learning analytics data and translate dashboard findings into actionable teaching decisions. Use when reviewing LMS data, quiz patterns, or engagement metrics.

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Guides security professionals in implementing defense-in-depth security architectures, achieving compliance with industry frameworks (SOC2, ISO27001, GDPR, HIPAA), conducting threat modeling and risk assessments, managing security operations and incident response, and embedding security throughout the SDLC.

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Assess an A-share portfolio company's AI readiness for China-focused private equity investments. Evaluates data infrastructure, technology stack, talent, and AI adoption opportunities in the Chinese market context. Triggers on "A股公司AI评估", "AI readiness China", "AI assessment portfolio company", "AI转型评估", or "artificial intelligence readiness [company]".

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Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", or "content audit".

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Monetization strategy for iOS/macOS apps. Covers readiness assessment, pricing model selection, tier structuring, free trial strategy, and implementation guidance. Use when deciding what to charge, how to price, or planning monetization end-to-end.

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Data quality assessment is an integral part of preparatory data analysis to ensure sound biological information retrieval. We present here the MatrixQCvis package, which provides shiny-based interactive visualization of data quality metrics at the per-sample and per-feature level. It is broadly applicable to quantitative omics data types that come in matrix-like format (features x samples). It enables the detection of low-quality samples, drifts, outliers and batch effects in data sets. Visualiz

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This package implements sampling, iteration, and input of FASTQ files. The package includes functions for filtering and trimming reads, and for generating a quality assessment report. Data are represented as DNAStringSet-derived objects, an

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Expert guidance for designing, assessing, and optimizing Azure workloads using Azure Well Architected. Covers design review checklists, recommendations, design principles, tradeoffs, service guides, workload patterns, and assessment questions. Use when designing AI, HPC, SaaS, AVD/AVS workloads, choosing regions/AZs, or configuring core Azure services, and other Azure Well Architected related development tasks.

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Amazon Buy Box strategy and optimization framework. Eligibility factor analysis, competitive pricing strategies, FBA vs FBM impact assessment, seller performance optimization, and Buy Box winning tactics. Use when the user asks about Amazon Buy Box, winning Buy Box, Buy Box eligibility, or Buy Box optimization.

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Amazon deal planning and promotional strategy optimization. Lightning Deals, Best Deals, Coupons, Prime Exclusive Discounts analysis and ROI calculation. Deal eligibility assessment, timing optimization, and promotional campaign planning. Use when the user asks about Amazon deals, Lightning Deals, promotional planning, deal strategy, or Amazon promotions.

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Comprehensive Amazon profit analysis and revenue optimization. Revenue waterfall analysis, hidden fee identification, ACoS impact assessment, return cost calculation, and profitability optimization strategies. Use when the user asks about Amazon profit analysis, profitability calculation, fee analysis, margin optimization, or revenue breakdown.

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Run a large-scale language migration with the six-step process: create the map and the rules, stress-test the rules, translate everything, compile, run it, match behavior. Use when the user wants to migrate, port, or rewrite a codebase from one language to another ("migrate this to Rust", "port our Python CLI to TypeScript", "should we rewrite this in Go?"), or asks for a migration feasibility assessment. Not for incremental JS→TS adoption — that needs no machinery — or single-file conversions.

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First-tier tech company P7 capability advisor for evaluating, coaching, and giving career advice against a P7 technical/product/expert profile. Use when the user asks for P7-level assessment, promotion readiness, capability gaps, resume/project review, interview preparation, or concrete growth advice based on first-tier tech company P7 expectations.

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First-tier tech company P8 capability advisor for evaluating, coaching, and giving career advice against a P8 senior expert, architect, or domain-owner profile. Use when the user asks for P8-level assessment, promotion readiness, capability gaps, project or resume review, interview preparation, or growth advice based on first-tier tech company P8 expectations.

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First-tier tech company P9 capability advisor for evaluating, coaching, and giving career advice against a P9 senior expert, director, or business/organization-level leader profile. Use when the user asks for P9-level assessment, promotion readiness, executive capability gaps, strategic project review, resume positioning, interview preparation, or growth advice based on first-tier tech company P9 expectations.

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Review dimensions and scoring for root cause analysis quality assessment

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Type-specific validation checklists, six quality characteristics, and quality gate thresholds for documentation assessment

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Critique dimensions, severity framework, verdict decision matrix, and review output format for documentation assessment reviews

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Requirements quality critique dimensions for peer review - confirmation bias detection, completeness validation, clarity checks, testability assessment, and priority validation

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Rollback procedures, risk assessment, pre/post-deployment validation, and contingency planning. Load when orchestrating deployment or preparing rollback plans. For deployment strategy details (canary, blue-green, rolling), see `cicd-and-deployment` skill.

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Use for authorized database security assessment covering PostgreSQL/MySQL/MSSQL/Mongo/Redis exposure, authz, UDF/command paths, and misconfiguration review.

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。