Cloud, CI/CD, monitoring, and deployment (7.1K skills)
LLM and ML model deployment for inference. Use when serving models in production, building AI APIs, or optimizing inference. Covers vLLM (LLM serving), TensorRT-LLM (GPU optimization), Ollama (local), BentoML (ML deployment), Triton (multi-model), LangChain (orchestration), LlamaIndex (RAG), and streaming patterns.
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Monitoring, logging, and tracing implementation using OpenTelemetry as the unified standard. Use when building production systems requiring visibility into performance, errors, and behavior. Covers OpenTelemetry (metrics, logs, traces), Prometheus, Grafana, Loki, Jaeger, Tempo, structured logging (structlog, tracing, slog, pino), and alerting.
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Design and implement Azure cloud architectures using best practices for compute, storage, databases, AI services, networking, and governance. Use when building applications on Microsoft Azure or migrating workloads to Azure cloud platform.
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Build professional command-line interfaces in Python, Go, and Rust using modern frameworks like Typer, Cobra, and clap. Use when creating developer tools, automation scripts, or infrastructure management CLIs with robust argument parsing, interactive features, and multi-platform distribution.
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Design cloud network architectures with VPC patterns, subnet strategies, zero trust principles, and hybrid connectivity. Use when planning VPC topology, implementing multi-cloud networking, or establishing secure network segmentation for cloud workloads.
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Implement GitOps continuous delivery for Kubernetes using ArgoCD or Flux. Use for automated deployments with Git as single source of truth, pull-based delivery, drift detection, multi-cluster management, and progressive rollouts.
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Optimize cloud infrastructure costs through FinOps practices, commitment discounts, right-sizing, and automated cost management. Use when reducing cloud spend, implementing budget controls, or establishing cost visibility across AWS, Azure, GCP, and Kubernetes environments.
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Manage DNS records, TTL strategies, and DNS-as-code automation for infrastructure. Use when configuring domain resolution, automating DNS from Kubernetes with external-dns, setting up DNS-based load balancing, or troubleshooting propagation issues across cloud providers (Route53, Cloud DNS, Azure DNS, Cloudflare).
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Selecting and implementing AWS services and architectural patterns. Use when designing AWS cloud architectures, choosing compute/storage/database services, implementing serverless or container patterns, or applying AWS Well-Architected Framework principles.
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Deployment patterns from Kubernetes to serverless and edge functions. Use when deploying applications, setting up CI/CD, or managing infrastructure. Covers Kubernetes (Helm, ArgoCD), serverless (Vercel, Lambda), edge (Cloudflare Workers, Deno), IaC (Pulumi, OpenTofu, SST), and GitOps patterns.
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Implement applications using Google Cloud Platform (GCP) services. Use when building on GCP infrastructure, selecting compute/storage/database services, designing data analytics pipelines, implementing ML workflows, or architecting cloud-native applications with BigQuery, Cloud Run, GKE, Vertex AI, and other GCP services.
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Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare. Originally from OpenAI's curated skills catalog.
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Deploy web projects to Netlify using the Netlify CLI (`npx netlify`). Use when the user asks to deploy, host, publish, or link a site/repo on Netlify, including preview and production deploys. Originally from OpenAI's curated skills catalog.
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Deploy applications and websites to Vercel. Use this skill when the user requests deployment actions such as "Deploy my app", "Deploy this to production", "Create a preview deployment", "Deploy and give me the link", or "Push this live". No authentication required - returns preview URL and claimable deployment link.
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Comprehensive quality gates, metrics analysis, and deployment readiness assessment for continuous quality assurance.
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QCSD Production Telemetry phase swarm for post-release production health assessment using DORA metrics, root cause analysis, defect prediction, and cross-phase feedback loops. Consumes CI/CD outputs (RELEASE/REMEDIATE/BLOCK decisions, release readiness metrics) and produces feedback signals to Ideation and Refinement.
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Use when monitoring in-sprint code quality with TDD adherence checks, complexity analysis, coverage gap detection, or defect prediction in the QCSD Development phase.
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Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges
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Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
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Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
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Retrieves up-to-date documentation, API references, and code examples for any developer technology. Use this skill whenever the user asks about a specific library, framework, SDK, CLI tool, or cloud service — even for well-known ones like React, Next.js, Prisma, Express, Tailwind, Django, or Spring Boot. Your training data may not reflect recent API changes or version updates. Always use for: API syntax questions, configuration options, version migration issues, "how do I" questions mentioning a library name, debugging that involves library-specific behavior, setup instructions, and CLI tool usage. Use even when you think you know the answer — do not rely on training data for API details, signatures, or configuration options as they are frequently outdated. Always verify against current docs. Prefer this over web search for library documentation and API details.
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Configure and collect crash dumps for modern .NET applications. USE FOR: enabling automatic crash dumps for CoreCLR or NativeAOT, capturing dumps from running .NET processes, setting up dump collection in Docker or Kubernetes, using dotnet-dump collect or createdump. DO NOT USE FOR: analyzing or debugging dumps, post-mortem investigation with lldb/windbg/dotnet-dump analyze, profiling or tracing, or for .NET Framework processes.
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Migrate a .NET 9 project or solution to .NET 10 and resolve all breaking changes. USE FOR: upgrading TargetFramework from net9.0 to net10.0, fixing build errors after updating the .NET 10 SDK, resolving source and behavioral changes in .NET 10 / C# 14 / ASP.NET Core 10 / EF Core 10, updating Dockerfiles for Debian-to-Ubuntu base images, resolving obsoletion warnings (SYSLIB0058-SYSLIB0062), adapting to SDK/NuGet changes (NU1510, PrunePackageReference), migrating System.Linq.Async to built-in AsyncEnumerable, fixing OpenApi v2 API changes, cryptography renames, and C# 14 compiler changes (field keyword, extension keyword, span overloads). DO NOT USE FOR: .NET Framework migrations, upgrading from .NET 8 or earlier (use migrate-dotnet8-to-dotnet9 first), greenfield .NET 10 projects, or cosmetic modernization. LOADS REFERENCES: csharp-compiler, core-libraries, sdk-msbuild (always); aspnet-core, efcore, cryptography, extensions-hosting, serialization-networking, winforms-wpf, containers-interop (selective).
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Migrate a .NET 10 project or solution to .NET 11 and resolve all breaking changes. This is a MIGRATION skill — use it when upgrading from .NET 10 to .NET 11, NOT for writing new programs. USE FOR: upgrading TargetFramework from net10.0 to net11.0, fixing build errors after updating the .NET 11 SDK, resolving source-breaking and behavioral changes in .NET 11 runtime, C# 15 compiler, and EF Core 11, adapting to updated minimum hardware requirements (x86-64-v2, Arm64 LSE), and updating CI/CD pipelines and Dockerfiles for .NET 11. DO NOT USE FOR: .NET Framework migrations, upgrading from .NET 9 or earlier, greenfield .NET 11 projects, or cosmetic modernization unrelated to the upgrade. NOTE: .NET 11 is in preview. Covers breaking changes through Preview 3.
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