「machine」の検索結果

Expert knowledge for Azure Database Migration Service development including troubleshooting, decision making, limits & quotas, security, integrations & coding patterns, and deployment. Use when planning Azure DMS migrations for MySQL, PostgreSQL, MongoDB, SSIS-to-Azure SQL, or hybrid workloads, and other Azure Database Migration Service related development tasks. Not for Azure Migrate (use azure-migrate), Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines).

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。

Expert knowledge for Azure HPC Cache development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring HPC Cache namespaces, NFS/Blob targets, client access, data ingest scripts, or cache failover, and other Azure HPC Cache related development tasks. Not for Azure Managed Lustre (use azure-managed-lustre), Azure NetApp Files (use azure-netapp-files), Azure Batch (use azure-batch), Azure Virtual Machines (use azure-virtual-machines).

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。

Expert knowledge for Azure Files development including best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when planning Azure File shares, File Sync tiering, NFS/SMB migrations, DR topologies, or RAG integrations, and other Azure Files related development tasks. Not for Azure Blob Storage (use azure-blob-storage), Azure NetApp Files (use azure-netapp-files), Azure Managed Lustre (use azure-managed-lustre), Azure Virtual Machines (use azure-virtual-machines).

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。

Expert knowledge for Azure Dev Box development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing Dev Box images, configuring pools/catalogs, securing access (RBAC/SSO), managing quotas, or fixing connectivity, and other Azure Dev Box 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).

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。

Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, limits & quotas, configuration, and deployment. Use when tuning Docker-based Anomaly Detector, ACI or IoT Edge deployments, univariate/multivariate APIs, or service limits, and other Azure AI Anomaly Detector related development tasks. Not for Azure AI Metrics Advisor (use azure-metrics-advisor), Azure Monitor (use azure-monitor), Azure Machine Learning (use azure-machine-learning).

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。

Expert knowledge for Azure Anyscale On Azure development including limits & quotas, security, configuration, and deployment. Use when authoring ARM templates, hardening images, configuring Private Link, or checking Anyscale regional availability, and other Azure Anyscale On Azure related development tasks. Not for Azure Databricks (use azure-databricks), Azure Machine Learning (use azure-machine-learning), Azure HDInsight (use azure-hdinsight).

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。

Expert knowledge for Azure Cloud Services development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing Cloud Services guest OS versions, Key Vault certs, .csdef/.cscfg configs, autoscale, or PowerShell automation, and other Azure Cloud Services related development tasks. Not for Azure App Service (use azure-app-service), Azure Virtual Machines (use azure-virtual-machines), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Functions (use azure-functions).

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。

Expert knowledge for Azure Analysis Services development including troubleshooting. Use when resolving server connectivity, firewall/VNet, DNS, client connection, or network error issues, and other Azure Analysis Services related development tasks. Not for Azure Synapse Analytics (use azure-synapse-analytics), Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines).

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。

Expert knowledge for Azure Copilot development including troubleshooting, decision making, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when sizing VMs, generating Bicep/Terraform, configuring Cosmos DB chat storage, or designing Azure networks, and other Azure Copilot related development tasks. Not for Azure Portal (use azure-portal), Azure Machine Learning (use azure-machine-learning), Azure DevOps (use azure-devops), Microsoft Foundry (use microsoft-foundry).

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。

Expert knowledge for Azure Business Process Tracking development including deployment. Use when creating CI/CD pipelines, automating builds, running tests, and deploying tracking solutions via DevOps tools, and other Azure Business Process Tracking related development tasks. Not for Azure Monitor (use azure-monitor), Azure Logic Apps (use azure-logic-apps), Azure Data Factory (use azure-data-factory), Azure Machine Learning (use azure-machine-learning).

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。

Expert knowledge for Azure Arc development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Arc-enabled Kubernetes, Arc SQL/data services, Agentic Retrieval APIs, resource bridge, or Edge Volumes, and other Azure Arc related development tasks. Not for Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Network (use azure-virtual-network), Azure Policy (use azure-policy).

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。

Expert knowledge for Azure Batch development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring Batch pools, autoscale, private networking, CMK encryption, or CI/CD for HPC/render jobs, and other Azure Batch related development tasks. Not for Azure Container Instances (use azure-container-instances), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Functions (use azure-functions), Azure Virtual Machines (use azure-virtual-machines).

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。

Expert knowledge for Azure AI Custom Vision development including best practices, decision making, limits & quotas, security, integrations & coding patterns, and deployment. Use when exporting Custom Vision models, calling prediction APIs, using ONNX/TensorFlow, managing CMK/RBAC, or Smart Labeler, and other Azure AI Custom Vision related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI services (use microsoft-foundry-tools), Azure Machine Learning (use azure-machine-learning), Azure AI Foundry Local (use microsoft-foundry-local).

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。

Expert knowledge for Azure Backup development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when protecting Azure VMs, AKS, SQL/SAP HANA, Files/Blobs, or disks with Azure Backup and restore automation, and other Azure Backup related development tasks. Not for Azure Site Recovery (use azure-site-recovery), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Network (use azure-virtual-network).

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。

Expert knowledge for Azure Container Instances development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and deployment. Use when configuring ACI standby pools, static IP networking, GPU containers, secure ACR pulls, or GitHub Actions deploys, and other Azure Container Instances related development tasks. Not for Azure Container Apps (use azure-container-apps), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure App Service (use azure-app-service), Azure Virtual Machines (use azure-virtual-machines).

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。

Expert knowledge for Azure Cloud Shell development including troubleshooting, limits & quotas, and security. Use when handling Cloud Shell storage mounts, session limits, file persistence, private VNet access, or RBAC setup, and other Azure Cloud Shell related development tasks. Not for Azure Portal (use azure-portal), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop), Azure DevOps (use azure-devops).

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。

Use when you need to generate Java project diagrams — including UML sequence diagrams, UML class diagrams, C4 model diagrams, UML state machine diagrams, UML Deployment Diagrams, ER (Entity Relationship) diagrams, and bounded-context diagrams — through a modular, step-based interactive process that adapts to your specific visualization needs. This should trigger for requests such as Generate UML diagram; Create sequence diagram; Create class diagram; Create state machine diagram; Create deployment diagram; Create C4 diagram; Create bounded-context diagram; Create context-map diagram. Part of Plinth Toolkit

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。

Machine learning development patterns, model training, evaluation, and deployment. Use when building ML pipelines, training models, feature engineering, model evaluation, or deploying ML systems to production.

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。

Diagrams and checkable docs from a codebase. Draws ERDs, C4 context/container/component views, API endpoint catalogues, lifecycle/state machines, and service-to-service call maps as a validated JSON spec plus a standalone HTML viewer, with Mermaid export. Imports OpenAPI, GraphQL SDL and Prisma; otherwise reads the code (NestJS, TypeORM, Express) and writes the spec. Use for: database diagram, ERD, data model, table relationships, C4 or architecture diagram, system context, API map, endpoint list, "show me the endpoints", status flow, state machine, allowed transitions, "what happens after X is approved", how services call each other, microservice map, Mermaid diagram. Also writes documentation as a fact graph: each statement carries its source and a computed confidence, and a drift check fails CI when the code moves. Use to document a system, write architecture or onboarding docs, or explain how a system works.

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。

Architecture patterns, design principles, and proven recipes for building robust robotics software. Use this skill when designing robot software architectures, choosing between behavioral frameworks, structuring perception-planning-control pipelines, implementing state machines, designing safety systems, or architecting multi-robot systems. Trigger whenever the user mentions behavior trees, finite state machines, subsumption architecture, sensor fusion, robot safety, watchdogs, heartbeats, graceful degradation, hardware abstraction layers, real-time constraints, or software architecture for robots. Also applies to sim-to-real transfer, digital twins, and robot fleet management.

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。

Executes GDPR Article 20 data portability requests, covering machine-readable format requirements (JSON, CSV, XML), direct controller-to-controller transfer mechanisms, and scope limitations to data provided by the subject on consent or contract basis. Activate for portability, data export, Art. 20, data transfer 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。

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.

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。

Check that this machine's agent team can work and say what is wrong in plain lines: tools installed, core skills installed, skill commands runnable, hooks configured, Reach seat live, a heartbeat running, both vendors' quota readable, temp space free. Checks only, never repairs. Use on a new machine, when agents stop reaching each other or a long run fails to start, or when the owner asks whether everything is healthy.

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。

Applies the reasoning style of Daphne Koller (machine learning pioneer, co-founder of Coursera, founder and CEO of Insitro). Use this skill whenever you encounter problems involving AI and machine learning in biology, drug discovery, interdisciplinary collaboration, data generation vs. data mining, or transitioning from academia to industry. Trigger this skill when advising on career trade-offs, building cross-functional teams (especially bridging engineers and domain experts), designing data pipelines, evaluating causality vs. correlation, or applying AI to physical systems ('where bits meet atoms'). Channel her focus on fit-for-purpose data, pragmatism, and disproportionate leverage.

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。