Cloud, CI/CD, monitoring, and deployment (6.8K skills)
Adds a complete blog feature to an existing Blazor WebAssembly Static Web App with Azure Functions backend and Azure File Share for markdown storage. Use when implementing blog functionality in .NET Blazor WASM projects with Azure infrastructure. Includes post listing, detail pages, markdown rendering, Azure Storage integration.
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Containerize an ASP.NET Core project by creating Dockerfile and .dockerfile files customized for the project.
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Comprehensive expertise for Azure Static Web Apps including architecture, configuration, API integration with Azure Functions, authentication, routing, deployment, and CI/CD. Use when building, configuring, deploying, or troubleshooting Azure Static Web Apps projects with frameworks like React, Angular, Vue, Blazor, or vanilla JavaScript.
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Helps create, configure, and deploy Azure Static Web Apps using the SWA CLI. Use when deploying static sites to Azure, setting up SWA local development, configuring staticwebapp.config.json, adding Azure Functions APIs to SWA, or setting up GitHub Actions CI/CD for Static Web Apps.
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Aspire skill covering the Aspire CLI, AppHost orchestration, service discovery, integrations, MCP server, VS Code extension, Dev Containers, GitHub Codespaces, templates, dashboard, and deployment. Use when the user asks to create, run, debug, configure, deploy, or troubleshoot an Aspire distributed application.
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Instrument a webapp to send useful telemetry data to Azure App Insights
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Expert guidance for developing cross-platform desktop applications with Avalonia UI framework. Use when building, debugging, or optimizing Avalonia apps including MVVM architecture, XAML design, data binding, styling, theming, custom controls, and cross-platform deployment for Windows, macOS, Linux, iOS, Android, and WebAssembly.
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Setup and initialization guide for developing AWS CDK (Cloud Development Kit) applications in Python. This skill enables users to configure environment prerequisites, create new CDK projects, manage dependencies, and deploy to AWS.
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INVOKE THIS SKILL for LLM-as-judge evaluation workflows on Arize: creating/updating evaluators, running evaluations on spans or experiments, tasks, trigger-run, column mapping, and continuous monitoring. Use when the user says: create an evaluator, LLM judge, hallucination/faithfulness/correctness/relevance, run eval, score my spans or experiment, ax tasks, trigger-run, trigger eval, column mapping, continuous monitoring, query filter for evals, evaluator version, or improve an evaluator prompt.
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Astro framework patterns, islands architecture, content collections, rendering strategies, and deployment. Use for: astro, islands architecture, content collections, astro cloudflare, view transitions, partial hydration, astrojs, SSG, SSR, hybrid rendering, astro adapter.
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Analyze Azure resources used in the app (IaC files and/or resources in a target rg) and optimize costs - creating GitHub issues for identified optimizations.
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INVOKE THIS SKILL when creating, reading, updating, or deleting Arize AI integrations. Covers listing integrations, creating integrations for any supported LLM provider (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM, custom), updating credentials or metadata, and deleting integrations using the ax CLI.
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Automatically issue/renew HTTPS certificates using Alibaba Cloud ESA DNS + acme.sh (including wildcard *.example.com + example.com), with optional installation to Nginx. Trigger this skill when the user mentions ESA, ATrustDNS, _acme-challenge, acme.sh, Let's Encrypt, No TXT record found, InvalidRecordNameSuffix, wildcard certificate, or Nginx certificate configuration.
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Prevents duplicate external actions (posts, replies, sends, transfers, deploys). Check before acting, record after. Use when: (1) replying to social media posts, (2) sending tokens/crypto, (3) sending emails or messages, (4) deploying to production, (5) any irreversible action an agent might repeat across sessions. Built by an AI agent who double-replied on X and double-sent airdrops.
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Proactive monitoring of Aave V3 borrow positions with liquidation alerts. Queries user collateral, debt, and health factor across chains (Ethereum, Polygon, Arbitrum, etc.). Sends urgent alerts to Telegram/Discord/Slack when health factor drops below configurable thresholds (critical at 1.05, warning at 1.2). Use when you need continuous monitoring of Aave positions, want alerts before liquidation risk occurs, or need periodic summaries of your borrowing health.
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Web scraping with Scrapling - HTTP fetching, stealth browser automation, Cloudflare bypass, and spider crawling via CLI and Python.
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Index a codebase with GitNexus and serve an interactive knowledge graph via web UI + Cloudflare tunnel.
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Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.
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Publish static sites to {slug}.here.now and store private files in cloud Drives for agent-to-agent handoff.
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Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.
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Modify, debug, or extend the s6-overlay supervision tree inside the Hermes Agent Docker image — adding new services, debugging profile gateways, understanding the Architecture B main-program pattern.
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Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.
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Public-records OSINT investigation framework — SEC EDGAR filings, USAspending contracts, Senate lobbying, OFAC sanctions, ICIJ offshore leaks, NYC property records (ACRIS), OpenCorporates registries, CourtListener court records, Wayback Machine archives, Wikipedia + Wikidata, GDELT news monitoring. Entity resolution across sources, cross-link analysis, timing correlation, evidence chains. Python stdlib only.
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Generate flat, minimal light/dark-aware SVG diagrams as standalone HTML files, using a unified educational visual language with 9 semantic color ramps, sentence-case typography, and automatic dark mode. Best suited for educational and non-software visuals — physics setups, chemistry mechanisms, math curves, physical objects (aircraft, turbines, smartphones, mechanical watches), anatomy, floor plans, cross-sections, narrative journeys (lifecycle of X, process of Y), hub-spoke system integrations (smart city, IoT), and exploded layer views. If a more specialized skill exists for the subject (dedicated software/cloud architecture, hand-drawn sketches, animated explainers, etc.), prefer that — otherwise this skill can also serve as a general-purpose SVG diagram fallback with a clean educational look. Ships with 15 example diagrams.
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