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Save MultiAssayExperiments to h5mu files supported by muon and mudata. Muon is a Python framework for multimodal omics data analysis. It uses an HDF5-based format for data storage.
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Provides efficient containers for storing and manipulating short genomic alignments (typically obtained by aligning short reads to a reference genome). This includes read counting, computing the coverage, junction detection, and working wit
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Expert knowledge for Azure Quotas development including limits & quotas. Use when checking storage account capacity, IOPS, throughput, portal views, or CLI-based quota increase requests, and other Azure Quotas related development tasks. Not for Azure Monitor (use azure-monitor), Azure Resource Manager (use azure-resource-manager), 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 SQL Server on Azure Virtual Machines development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when planning SQL VM vs Managed Instance, Always On/FCI HADR, Azure storage/backups, Key Vault/Entra auth, or KQL telemetry, and other SQL Server on Azure Virtual Machines related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), Azure Virtual Machines (use azure-virtual-machines), Azure Data Science Virtual Machines (use azure-data-science-vm).
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 Service Connector development including troubleshooting, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when wiring Azure compute to Redis, databases, storage, messaging, AI services, or third‑party endpoints, and other Azure Service Connector related development tasks. Not for Azure API Management (use azure-api-management), Azure Connector Namespace (use azure-connector-namespace), Azure Logic Apps (use azure-logic-apps), Azure Service Bus (use azure-service-bus).
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 Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using AutoML, Prompt Flow, online/batch endpoints, vector stores/RAG, or Model Catalog in Azure ML, and other Azure Machine Learning related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure Data Science Virtual Machines (use azure-data-science-vm), 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 Operator Nexus development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and deployment. Use when managing Nexus clusters, fabric ACLs/BGP, isolation domains, near‑edge storage, or upgrade workflows, and other Azure Operator Nexus related development tasks. Not for Azure Operator Insights (use azure-operator-insights), Azure Operator Service Manager (use azure-operator-service-manager), Azure Networking (use azure-networking), Azure Virtual Network Manager (use azure-virtual-network-manager).
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 Large Instances development including troubleshooting, limits & quotas, and integrations & coding patterns. Use when configuring Epic SKUs, sizing volume groups, tuning EHR storage, or resolving Epic–ALI connectivity/perf issues, and other Azure Large Instances related development tasks. Not for Azure Baremetal Infrastructure (use azure-baremetal-infrastructure), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Machine Scale Sets (use azure-vm-scalesets), Azure HPC Cache (use azure-hpc-cache).
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 Managed Applications development including limits & quotas, security, configuration, and deployment. Use when designing createUiDefinition UIs, JIT access, managed identities, StorageAccountSelector, or Bicep-based catalog publishing, and other Azure Managed Applications related development tasks. Not for Azure Blueprints (use azure-blueprints), Azure Resource Manager (use azure-resource-manager), Azure Lighthouse (use azure-lighthouse), Azure Partner Solutions (use azure-partner-solutions).
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 Defender For Cloud development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when securing VMs/containers/storage/SQL, enabling plans, tuning alerts, exporting via APIs/ARG, or integrating SIEM/XDR, and other Azure Defender For Cloud related development tasks. Not for Azure Security (use azure-security), Azure Sentinel (use azure-sentinel), Azure DDoS Protection (use azure-ddos-protection), Azure External Attack Surface Management (use azure-external-attack-surface-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。
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).
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 Durable Task development including best practices, decision making, architecture & design patterns, limits & quotas, configuration, integrations & coding patterns, and deployment. Use when building Durable orchestrations with Azure Storage/SQL/Netherite, versioning deployments, or using instance APIs, and other Azure Durable Task related development tasks. Not for Azure Functions (use azure-functions), Azure Logic Apps (use azure-logic-apps), Azure App Service (use azure-app-service), Azure Service Fabric (use azure-service-fabric).
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 Content Understanding in Foundry Tools development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when designing Content Understanding analyzers, RAG document flows, agentic workflows, REST/SDK calls, or Foundry deployments, and other Azure Content Understanding in Foundry Tools related development tasks. Not for Azure Speech in Foundry Tools (use azure-speech), Azure AI Search (use azure-cognitive-search), Azure AI Document Intelligence (use azure-document-intelligence), Azure AI Video Indexer (use azure-video-indexer).
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Expert guidance for designing Azure solutions using Azure Architecture. Covers reference architectures, solution ideas, design patterns, technology choices, architecture styles, best practices, anti-patterns, example workloads, and migration guides. Use when designing RAG/GenAI, AKS, SAP or mainframe migrations, HA/DR topologies, or secure hybrid networks, and other Azure Architecture related development tasks.
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。
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).
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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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Detect suspected manipulation on prediction markets over the past 3 days by cross-referencing price/volume/comment anomalies with multilingual local-press coverage
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Read your Robinhood Agentic brokerage account via the Robinhood Trading MCP - portfolio, buying power, positions, and order history - and place a single operator-instructed trade. OAuth Connect via the dashboard MCP panel.
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5 concrete real-life actions, leverage-scored against open loops with specificity and anti-fluff gates
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Expand a hard-to-build niche list from ~10 known-good seed companies into a full qualified TAM. Seed fingerprinting (how do good-fit companies ACTUALLY show up in the company database's filters) → lookalike generation (Prospeo company_lookalike, Exa findSimilar, Parallel.ai entity search) → filter mining with a precision/volume scorecard → wide pull with auto-sharding → cheap-AI qualification → live-website verification → client transparency report. Use when a vertical list feels "too small" (medical groups, hedge funds, Medicare brokerages), when known good-fit companies don't show up in keyword searches, or when someone says "expand this list", "the TAM should be bigger", "find more companies like these".
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Pre-send quality scorecard for any lead list. Grades duplicate rate, title diversity, bad-title patterns, catch-all domain density, ICP fit, email verification coverage. Outputs a letter grade + action items BEFORE you send. Catches bad lists before they burn inboxes. Run after email enrichment, before Smartlead upload.
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Writes the character-performance layer of a video prompt as behavior under pressure, not displayed emotion — objective, obstacle, tactics, beats, subtext, listening, body/status/proxemics, and mandatory eye life. Produces a reusable 150–220-word acting master profile per character plus a per-scene rewrite of it, and a locked voice prompt. Use whenever a prompt needs acting, performance, or emotion direction; whenever characters read wooden, dead-eyed, or 'AI'; whenever a character must stay themselves across many shots; or when the user asks for character behavior, mannerisms, tics, a gait, or how someone reacts. Pairs with higgsfield-facs (muscle-level AU codes) and higgsfield-seedance (the prompt the paragraph goes into).
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Write high-quality JUnit 5 tests with AssertJ assertions. Use when user says "add tests", "write tests", "improve test coverage", or when reviewing/creating test classes for Java code.
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。