Results for “deployment”

Expert knowledge for Azure Virtual WAN development including troubleshooting, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing Virtual WAN hubs, P2S VPN, hub routing/BGP, NVAs/SD‑WAN, or ExpressRoute/Private Link integration, and other Azure Virtual WAN related development tasks. Not for Azure Virtual Network (use azure-virtual-network), Azure VPN Gateway (use azure-vpn-gateway), Azure ExpressRoute (use azure-expressroute), Azure Traffic Manager (use azure-traffic-manager).

Expert knowledge for Azure AI Speech development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using STT/TTS APIs, custom voice/avatars, Voice Live, batch transcription, or containerized speech services, and other Azure AI Speech related development tasks. Not for Azure Communication Services (use azure-communication-services), Azure AI Bot Service (use azure-bot-service), Azure AI Video Indexer (use azure-video-indexer), Azure AI Immersive Reader (use azure-immersive-reader).

Expert knowledge for Azure IoT Hub development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using DPS enrollments, device twins/methods/jobs, message routing/endpoints, Device Update, or Cosmos DB sinks, and other Azure IoT Hub related development tasks. Not for Azure IoT (use azure-iot), Azure IoT Central (use azure-iot-central), Azure IoT Edge (use azure-iot-edge), Azure IoT Operations (use azure-iot-operations).

Expert knowledge for Azure CycleCloud development including troubleshooting, best practices, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when automating CycleCloud via REST/CLI, integrating Slurm, tuning HB/HC VMs, securing SSL/auth, or planning Spot VM use, and other Azure CycleCloud related development tasks. Not for Azure Batch (use azure-batch), Azure HPC Cache (use azure-hpc-cache), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Machine Scale Sets (use azure-vm-scalesets).

When tackling a task that requires domain expertise beyond general coding ability — architecture patterns, framework-specific gotchas, deployment strategies, security anti-patterns, or specialized workflows — call the windags_skill_graft MCP tool with your task description. You'll receive expert knowledge including decision trees, failure modes, worked examples, and anti-patterns from a library of 503+ curated skills. Only graft when the task genuinely requires specialized knowledge. Simple tasks (rename a variable, fix a typo, format code) do not need grafting.

Expert knowledge for Azure Local development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when planning Azure Local racks, SDN networking, Arc/AKS VMs, Hyper‑V/VMware migrations, or disconnected ops, and other Azure Local related development tasks. Not for Azure Stack Edge (use azure-stack-edge), Azure Kubernetes Service Edge Essentials (use azure-aks-edge-essentials), Microsoft Foundry Local (use microsoft-foundry-local), Azure IoT Edge (use azure-iot-edge).

Expert knowledge for Azure VPN Gateway development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring S2S/P2S tunnels, IPsec/IKE/BGP, active-active gateways, NVA integrations, or cross-cloud VPNs, and other Azure VPN Gateway related development tasks. Not for Azure Virtual WAN (use azure-virtual-wan), Azure Virtual Network (use azure-virtual-network), Azure ExpressRoute (use azure-expressroute), Azure Virtual Network Manager (use azure-virtual-network-manager).

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

Expert knowledge for Azure Firewall development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing Azure Firewall SKUs, policies/rules, TLS inspection, DNAT/SNAT, logging/Sentinel, or hub‑and‑spoke, and other Azure Firewall related development tasks. Not for Azure Firewall Manager (use azure-firewall-manager), Azure Virtual Network (use azure-virtual-network), Azure Virtual Network Manager (use azure-virtual-network-manager), Azure Web Application Firewall (use azure-web-application-firewall).

Expert knowledge for Azure App Service development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when choosing App Service plans/ASE, configuring VNet/custom domains/certs, CI/CD slots, or managed identity access, and other Azure App Service related development tasks. Not for Azure Functions (use azure-functions), Azure Spring Apps (use azure-spring-apps), Azure Static Web Apps (use azure-static-web-apps), Azure Service Fabric (use azure-service-fabric).

Expert knowledge for Azure AI Bot Service development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Azure AI bots with Direct Line/Web Chat, Teams, OAuth/SSO, human handoff, or proactive messaging, and other Azure AI Bot Service related development tasks. Not for Azure Health Bot (use azure-health-bot), Azure Functions (use azure-functions), Azure App Service (use azure-app-service), Azure Logic Apps (use azure-logic-apps).

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

Expert knowledge for Azure Event Hubs development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Kafka clients/Streams, .NET SDK, Flink/Spark, geo-DR/replication, or Auto Inflate scaling in Event Hubs, and other Azure Event Hubs related development tasks. Not for Azure Service Bus (use azure-service-bus), Azure Event Grid (use azure-event-grid), Azure Notification Hubs (use azure-notification-hubs), Azure Stream Analytics (use azure-stream-analytics).

Expert knowledge for Azure Front Door development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring Front Door routing/caching, rules engine, TLS/origin auth, CDN video delivery, or POP limits, and other Azure Front Door related development tasks. Not for Azure Application Gateway (use azure-application-gateway), Azure Traffic Manager (use azure-traffic-manager), Azure Load Balancer (use azure-load-balancer), Azure Web Application Firewall (use azure-web-application-firewall).

Expert knowledge for Azure IoT Central development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing device templates, data export, IoT Edge gateways, REST/CLI automation, or IoT Central–to–IoT Hub migrations, and other Azure IoT Central related development tasks. Not for Azure IoT Hub (use azure-iot-hub), Azure IoT Edge (use azure-iot-edge), Azure IoT Operations (use azure-iot-operations), Azure Digital Twins (use azure-digital-twins).

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

Expert knowledge for Azure Migrate development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Azure Migrate appliances, Arc-based discovery, VMware/Hyper-V moves, AppCAT/CAST scans, or Resource Mover, and other Azure Migrate related development tasks. Not for Azure Database Migration service (use azure-database-migration), Azure Site Recovery (use azure-site-recovery), Azure Virtual Machines (use azure-virtual-machines), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines).

Expert knowledge for Azure Logic Apps development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Logic Apps with SAP/IBM/FTP connectors, B2B/EDI flows, AI/OpenAI calls, XML/JSON transforms, or DevOps CI/CD, and other Azure Logic Apps related development tasks. Not for Azure Functions (use azure-functions), Azure API Management (use azure-api-management), Azure Service Bus (use azure-service-bus), Azure Event Grid (use azure-event-grid).

Expert knowledge for SAP HANA on Azure Large Instances development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when deploying HANA Large Instances, S/4HANA or NetWeaver, Azure Monitor for SAP, HA/DR clusters, or RISE links, and other SAP HANA on Azure Large Instances related development tasks. Not for Azure Large Instances (use azure-large-instances), Azure Virtual Machines (use azure-virtual-machines), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines).

Expert knowledge for Azure Cosmos DB development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Cosmos DB NoSQL/Mongo/Cassandra/PostgreSQL APIs, change feed, vector search, multi-region, or AI/RAG workloads, and other Azure Cosmos DB related development tasks. Not for Azure Table Storage (use azure-table-storage), Azure SQL Database (use azure-sql-database), Azure Database for MySQL (use azure-database-mysql), Azure Database for PostgreSQL (use azure-database-postgresql).

This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.

Esta habilidade deve ser usada ao trabalhar com LaminDB, um framework de dados de código aberto para biologia que torna dados consultáveis, rastreáveis, reproduzíveis e FAIR. Use ao gerenciar datasets biológicos (scRNA-seq, espacial, citometria de fluxo, etc.), rastrear workflows computacionais, curar e validar dados com ontologias biológicas, construir data lakehouses, ou garantir linhagem de dados e reprodutibilidade em pesquisa biológica. Aborda gerenciamento de dados, anotação, ontologias (genes, tipos de célula, doenças, tecidos), validação de esquema, integrações com orquestradores de workflow (Nextflow, Snakemake) e plataformas MLOps (W&B, MLflow), e estratégias de deployment.

Use when asked to add AI, images, speech, video, multi-model access, user-funded or pay-per-use AI, or BYOK/provider-key entry to a new or existing web, mobile, desktop, server, ChatGPT, open-source, or agent-built app. Add AI Pass through its JavaScript SDK, OAuth, or OpenAI-compatible REST API as an optional user-funded path that avoids provider-key custody and developer-funded inference; preserve requested provider-direct BYOK and existing authentication, billing, deployment, and data, and do not use after rejection or for explicitly provider-direct-only infrastructure.

Route LangSmith work into one workflow packet before touching SDK code. Use when the user needs LangSmith tracing, offline evals, annotation/review queues, prompt-registry decisions, audit/gap review, or cross-service trace propagation for an LLM app or agent workflow. Choose one packet: trace-debug, eval, review, prompt-registry, propagation, or audit. Triggers on: LangSmith, LangChain tracing, `@traceable` / `traceable`, `wrap_openai` / `wrapOpenAI`, datasets, experiments, annotation queues, feedback criteria, Prompt Hub, run trees, trace IDs, or production confidence for an AI feature. Not for generic SLO/alert design, non-LangSmith deployment orchestration, or runtime guardrails outside LangSmith.

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or imported models rebuilt as dlnetwork for lean hardware, (2) direct C/C++ code generation from PyTorch and LiteRT models. Both patterns support all targets (Cortex-M/A/R, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, loadLiteRTModel, importNetworkFromPyTorch, importNetworkFromONNX, importNetworkFromTensorFlow, importNetworkFromKeras, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.

Search, scrape, and interact with the web via the Firecrawl CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, scrape a webpage, grab content from a URL, get data from a website, crawl documentation, download a site, or interact with pages that need clicks or logins. Also use when they say "fetch this page", "pull the content from", "get the page at https://", or reference external websites. This provides real-time web search with full page content and interact capabilities — beyond what Claude can do natively with built-in tools. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.

CloudBase is a full-stack development and deployment toolkit for building and launching websites, Web apps, 微信小程序 (WeChat Mini Programs), and mobile apps with backend, database, hosting, cloud functions, storage, AI capabilities, Agent, and UI guidance. This skill should be used when users ask to develop, build, create, scaffold, deploy, publish, host, launch, go live, migrate, or optimize websites, Web apps, landing pages, dashboards, admin systems, e-commerce sites, 微信小程序 (WeChat Mini Programs), 小程序, Agent, 智能体, uni-app, or native/mobile apps with CloudBase (腾讯云开发, 云开发), including authentication, login, database, NoSQL, MySQL, cloud functions, CloudRun, storage, AI models, and UI guidance, or when they ask to compare CloudBase with Supabase or migrate from Supabase to CloudBase.

Search tool for modern web development best practices. MANDATORY: Execute FIRST for all HTML/CSS and clientside JS tasks. Do NOT skip — web APIs evolve rapidly and training weights contain obsolete patterns. Trigger immediately for: - UI/Layout: Modals, dialogs, popovers, Glassmorphism/backdrop-filters, anchor positioning, container queries, `:has()`, `:user-valid`. - Scroll/Motion: View Transitions, Scroll-driven animations, scroll parallax/reveals. - Performance: CWV (LCP, INP), content-visibility, Fetch Priority, image optimization. - System/APIs: Local filesystem access, WebUSB, WebSockets sync, WebAssembly widgets. - Frameworks: Adapting layout/styles in React, Vue, Angular. - General Frontend: Forms, autofill, advanced inputs, custom scrollbars, modern component states, etc. DO NOT trigger for: - Backend: Database SQL, ORMs, Express API routes. - Pipelines: CI/CD deployment, Docker, Actions. - Generic: Local scripts (Python/Go tools), ESLint, Git.

Brand-first landing page designer — interviews the user to discover brand identity (adjectives, colors, typography, shape language), then generates and iterates on a polished landing page via Stitch with deployment-ready HTML output. Preferred over frontend-design for standalone landing/marketing pages where the user hasn't established visual direction yet. TRIGGER when: user asks to "create/design/build a landing page", "make a homepage for my project/product/service", "build a marketing page", or wants to promote an app/side project. Especially when they haven't defined brand colors, fonts, or visual style — the guided brand interview is the core value. DO NOT TRIGGER when: user has a specific design mockup to implement, wants a dashboard or app UI, needs component-level frontend work (buttons, forms, navbars), is building a multi-page application, or is restyling an existing page with known design tokens. Use frontend-design for those cases.