「integrate」の検索結果

Analyzes how multiple regulations interact for a specific product, service, or business model. Identifies where obligations overlap, reinforce, complement, duplicate, or conflict; builds a priority matrix; produces an integrated compliance timeline; and estimates the total compliance burden. Use when (1) scoping a new product or service against the full regulatory landscape before launch, (2) conducting M&A due diligence on a target's multi-regulation exposure, (3) building a strategic compliance roadmap where single-regulation analyses miss the interactions, (4) advising on complex situations where regulations touch the same conduct from different angles, or (5) estimating budget and resourcing for multi-regulation compliance. Primary coverage of EU digital regulation (GDPR, Data Act, AI Act, CRA, NIS2, DORA, DMA, DSA, ePrivacy) and national implementations; the framework extends to any jurisdiction where overlapping regulatory regimes apply to the same activity.

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Use when security verification is needed - pre-commit security checks, vulnerability scanning, STRIDE threat analysis. Integrates with /handoff-verify --security and /commit-push-pr. CWE Top 25 based.

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Anchor a multidisciplinary unit in a real-world phenomenon that requires multiple subject lenses to understand. Use when designing integrated or phenomenon-based units across disciplines.

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Map curriculum connections across multiple subjects for a real-world problem or authentic context. Use when planning cross-curricular projects or connecting content to real issues.

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Integrate the Temps Node.js SDKs for server-side platform access, KV storage, and Blob storage. Use when the user wants to: (1) Call the Temps platform API from Node.js (deployments, projects, analytics, session replay, etc.), (2) Use Temps KV (key-value) storage, (3) Use Temps Blob storage for files, (4) Server-side integration with a Temps project, (5) Backend access to Temps resources. Triggers: "temps node sdk", "temps kv", "temps blob", "backend integration", "node.js temps", "@temps-sdk/node-sdk".

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Three-statement financial model for A-share stocks. Adapts the standard 3-statement-model methodology for Chinese accounting standards (CAS), Chinese GAAP differences, and AkShare-sourced financials. Use instead of the original 3-statement-model skill when building integrated IS/BS/CF models for Chinese listed companies.

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Create new China-specific financial skills following the established patterns and conventions. Use this meta-skill to scaffold new china-* skills that integrate with iFind MCP (Tier-1) and AkShare MCP (Tier-2 fallback), follow CAS accounting standards, and adapt workflows for the Chinese market. Triggers on "创建中国skill", "新建A股skill", "create china skill", "new china-skill", "制作skill", or when creating any new china-* skill.

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Build Qwen Image 2512 text-to-image workflows with QwenImageIntegratedKSampler, separate component loading, lightning LoRAs, and fine-tuned model variants

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Integrate your app with iOS Visual Intelligence for camera-based search and object recognition. Use when adding visual search capabilities.

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A robust and outlier-aware method for testing differential tissue composition from single-cell data. This model can infer changes in tissue composition and heterogeneity, and can produce realistic data simulations based on any existing dataset. This model can also transfer knowledge from a large set of integrated datasets to increase accuracy further.

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The 'msa' package provides a unified R/Bioconductor interface to the multiple sequence alignment algorithms ClustalW, ClustalOmega, and Muscle. All three algorithms are integrated in the package, therefore, they do not depend on any externa

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This package aims to integrate GWAS-derived SNPs and coexpression networks to mine candidate genes associated with a particular phenotype. For that, users must define a set of guide genes, which are known genes involved in the studied phenotype. Additionally, the mined candidates can be given a score that favor candidates that are hubs and/or transcription factors. The scores can then be used to rank and select the top n most promising genes for downstream experiments.

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Methods to infer clonal tree configuration for a population of cells using single-cell RNA-seq data (scRNA-seq), and possibly other data modalities. Methods are also provided to assign cells to inferred clones and explore differences in gene expression between clones. These methods can flexibly integrate information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. A flexible beta-binomial error model that accounts for stoc

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This package provides a workflow for the use of EaSIeR tool, developed to assess patients' likelihood to respond to ICB therapies providing just the patients' RNA-seq data as input. We integrate RNA-seq data with different types of prior knowledge to extract quantitative descriptors of the tumor microenvironment from several points of view, including composition of the immune repertoire, and activity of intra- and extra-cellular communications. Then, we use multi-task machine learning trained in

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This R package supports interactive visualization of multi-channel images and segmentation masks generated by imaging mass cytometry and other highly multiplexed imaging techniques using shiny. The cytoviewer interface is divided into image-level (Composite and Channels) and cell-level visualization (Masks). It allows users to overlay individual images with segmentation masks, integrates well with SingleCellExperiment and SpatialExperiment objects for metadata visualization and supports image do

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Genomic data analyses requires integrated visualization of known genomic information and new experimental data. Gviz uses the biomaRt and the rtracklayer packages to perform live annotation queries to Ensembl and UCSC and translates this to

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Expert knowledge for Azure VMware Solution development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring AVS networking/storage, HCX migrations, Horizon/VDI, vSAN clusters, or Azure-integrated backups, and other Azure VMware Solution related development tasks. Not for Azure Virtual Machines (use azure-virtual-machines), Azure Stack Edge (use azure-stack-edge), Azure Nutanix (use azure-nutanix), Azure Red Hat OpenShift (use azure-redhat-openshift).

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Expert knowledge for Azure Lab Services development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring lab plans, VM templates/schedules, VNet-integrated labs, GPU/nested virtualization, or Canvas/Teams integration, and other Azure Lab Services related development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop).

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Expert knowledge for Azure HDInsight development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when working with HDInsight Spark/Hive/Kafka/HBase clusters, Ambari/Oozie pipelines, or Azure-integrated storage/BI, and other Azure HDInsight related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure Stream Analytics (use azure-stream-analytics).

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Amazon listing builder and optimizer for sellers. Two modes: (A) Create — build keyword-optimized listings from scratch using keyword lists + product characteristics + AI copywriting, (B) Optimize — audit existing listings, find keyword gaps, score across 8 dimensions, and rewrite with missing keywords. Integrates with amazon-keyword-research for keyword input. Works on 12 Amazon marketplaces. No API key required. Use when: (1) creating a new Amazon listing from keywords, (2) auditing an existing listing for SEO and conversion, (3) checking keyword coverage in title/bullets/description, (4) generating listing copy with target keywords and tone, (5) comparing listings against competitors, (6) preparing a listing for launch or relaunch.

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Amazon PPC campaign builder and optimizer for sellers. Two modes: (A) Build — design a complete campaign structure from scratch with keyword groupings, bid calculations, and negative keyword lists, (B) Optimize — audit existing campaigns using search term reports, identify keyword funnel opportunities, calculate bid adjustments, and generate a week-by-week action plan. Integrates with amazon-keyword-research for keyword input. No API key required. Use when: (1) setting up Amazon PPC campaigns for a new product, (2) auditing existing campaign performance and ACoS, (3) optimizing keyword bids and negative keywords, (4) building Auto/Manual/Exact campaign structures, (5) analyzing search term reports for opportunities, (6) calculating break-even ACoS and target ACoS, (7) scaling profitable campaigns to Sponsored Brands or Display.

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Write how-to guides and tutorials that naturally integrate affiliate product recommendations. Triggers on: "write a how-to guide", "tutorial for [task]", "step by step guide to [goal]", "how to [verb] with [product]", "write a tutorial blog post", "guide on how to [task]", "beginner guide to [topic]", "walkthrough for [product]", "write an educational article", "how do I [task] blog post", "write a tutorial that promotes [product]".

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Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

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Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

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