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Found 462 Skills
Install and configure NVIDIA NemoClaw (sandboxed OpenClaw agent platform) on Linux. Handles cloudflared tunnels, Docker cgroup fixes, OpenShell, sandbox creation, remote access via Cloudflare Tunnel, and known bug workarounds. Triggers: "install nemoclaw", "setup nemoclaw", "nvidia nemoclaw", "openclaw setup", "nemoclaw on spark", "nemoclaw on dgx".
Expert knowledge for Azure Translator development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Translator text/document APIs, custom models, glossaries, Docker containers, or Power Automate flows, and other Azure Translator related development tasks. Not for Azure AI Language (use azure-language-service), Azure AI Speech (use azure-speech), Azure AI Immersive Reader (use azure-immersive-reader), Azure AI Search (use azure-cognitive-search).
Create optimized, secure multi-stage Dockerfiles for React applications (Vite, CRA, Next.js static). Use when (1) creating a new Dockerfile for a React project, (2) containerizing a React/Vite application, (3) optimizing an existing React Dockerfile, (4) setting up Docker for React with Nginx, or (5) user mentions React and Docker/container together.
CI/CD pipeline design, containerization, and infrastructure management. Handles Docker, Kubernetes, monitoring setup (Prometheus/Grafana), and infrastructure-as-code (Terraform/Pulumi).
Utility skill to detect Magento development environment and determine command wrapper. This skill should be used by other skills that need to execute shell commands in the Magento environment. It detects Warden, docker-magento, DDEV, and local environments and provides the appropriate command wrapper.
Cloud GPU processing via RunPod serverless. Use when setting up RunPod endpoints, deploying Docker images, managing GPU resources, troubleshooting endpoint issues, or understanding costs. Covers all 5 toolkit images (qwen-edit, realesrgan, propainter, sadtalker, qwen3-tts).
Configures .NET CI/CD pipelines (GitHub Actions with setup-dotnet, NuGet cache, reusable workflows; Azure DevOps with DotNetCoreCLI, templates, multi-stage), containerization (multi-stage Dockerfiles, Compose, rootless), packaging (NuGet authoring, source generators, MSIX signing), release management (NBGV, SemVer, changelogs, GitHub Releases), and observability (OpenTelemetry, health checks, structured logging, PII). Spans 18 topic areas. Do not use for application-layer API or UI implementation patterns.
Publish and deploy C# MCP servers. Covers NuGet packaging for stdio servers, Docker containerization for HTTP servers, Azure Container Apps and App Service deployment, and publishing to the official MCP Registry. USE FOR: packaging stdio MCP servers as NuGet tools, creating Dockerfiles for HTTP MCP servers, deploying to Azure Container Apps or App Service, publishing to the MCP Registry at registry.modelcontextprotocol.io, configuring server.json for MCP package metadata, setting up CI/CD for MCP server publishing. DO NOT USE FOR: publishing general NuGet libraries (not MCP-specific), general Docker guidance unrelated to MCP, creating new servers (use mcp-csharp-create), debugging (use mcp-csharp-debug), writing tests (use mcp-csharp-test).
Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with container-first architecture for reproducible benchmarking.
Run GPU workloads on Modal — training, fine-tuning, inference, batch processing. Zero-config serverless: no SSH, no Docker, auto scale-to-zero. Use when user says "modal run", "modal training", "modal inference", "deploy to modal", "need a GPU", "run on modal", "serverless GPU", or needs remote GPU compute.
Build, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community grants. Use whenever the user asks to create or host an app on Hugging Face, port code onto ZeroGPU, fix a Space that won't build or run, or otherwise work with `hf spaces …`, `@spaces.GPU`, Space README frontmatter, or the `spaces` Python package.
Use when the user wants to store, retrieve, search, or manage files in agent-fs — an agent-first filesystem backed by S3. Triggers on: "save this to agent-fs", "find that file", "store this document", "search agent-fs", "list my files", "show version history", "revert file", "set up agent-fs", "get a signed url", "share this file", "manage members", "invite user", "list members", "remove member", "update role", file persistence for agents, shared agent filesystem, or any mention of the agent-fs CLI. Also use when the user needs to manage drives, manage org/drive members, generate presigned URLs, check recent activity, or use semantic search across stored files. Also use when the user wants to run SQL over stored data files ("query this csv", "sql over my files", "duckdb", "aggregate the parquet file", "query the sqlite db", "join these spreadsheets"). Also use when the user wants to mount or unmount agent-fs as a Linux FUSE filesystem ("mount agent-fs", "fuse mount", "fuse", "remote mount", "sandbox mount", "expose drives as files", "use cat/grep/mv on my agent-fs files", "umount the drive", "mount a remote drive", "mount from sprite", "mount from e2b", "mount from hetzner"). Also use when the user wants to use agent-fs as a just-bash filesystem. Also use when the user wants to set up agent-fs without Docker or S3 ("local filesystem backend", "filesystem storage", "no docker", "onboard --filesystem", "store files on disk"). If the user mentions agent-fs in any context, always consult this skill.