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Found 1,981 Skills
Essential CloudBase (TCB, Tencent CloudBase, 云开发, 微信云开发) development guidelines. MUST read when working with CloudBase projects, developing web apps, mini programs, backend services, fullstack development, static deployment, cloud functions, mysql/nosql database, authentication, cloud storage, web search or AI(LLM streaming) using CloudBase platform. Great supabase alternative.
Expert knowledge for Azure Synapse Analytics development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building, debugging, or optimizing Azure Synapse Analytics applications. Not for Azure Data Factory (use azure-data-factory), Azure Data Explorer (use azure-data-explorer), Azure Databricks (use azure-databricks), Azure Stream Analytics (use azure-stream-analytics).
This skill should be used when the user asks to "build an MCP server", "create an MCP", "make an MCP integration", "wrap an API for Claude", "expose tools to Claude", "make an MCP app", or discusses building something with the Model Context Protocol. It is the entry point for MCP server development — it interrogates the user about their use case, determines the right deployment model (remote HTTP, MCPB, local stdio), picks a tool-design pattern, and hands off to specialized skills.
Use KWC CLI (kd) to translate user requirements into deliverable KWC projects, components, page metadata, environment configurations, deployment and debugging results. This Skill is used when an Agent needs to initialize or extend a KWC project via scaffolding, split functions into KWC components, create or update *.page-meta.kwp, configure kd env, deploy metadata to the target environment, or guide the full process from requirements to KWC page rendering.
Expert knowledge for Azure Static Web Apps development including troubleshooting, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when wiring SWA APIs to Azure DBs, configuring custom domains/auth, CI/CD, preview slots, or Front Door/CDN, and other Azure Static Web Apps related development tasks. Not for Azure App Service (use azure-app-service), Azure Functions (use azure-functions), Azure Container Apps (use azure-container-apps), Azure Kubernetes Service (AKS) (use azure-kubernetes-service).
Clarity pre-deployment validation — syntax checking, deprecated keyword detection, sender check analysis, error propagation review, and test verification.
CLIP vision-language model for image-text retrieval, zero-shot classification, embedding extraction, ONNX export, and TensorRT deployment. Use when fine-tuning or training CLIP, running zero-shot classification, computing image embeddings, or deploying CLIP to ONNX/TensorRT.
Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.
Implement GitOps workflows with ArgoCD and Flux for automated, declarative Kubernetes deployments with continuous reconciliation. Use when implementing GitOps practices, automating Kubernetes deployments, or setting up declarative infrastructure management.
Design, organize, and manage Helm charts for templating and packaging Kubernetes applications with reusable configurations. Use when creating Helm charts, packaging Kubernetes applications, or implementing templated deployments.
Helm chart development patterns for packaging and deploying Kubernetes applications. Use when creating reusable Helm charts, managing multi-environment deployments, or building application catalogs for Kubernetes.
Next.js environment variable management with file precedence, variable types, and deployment configurations. Use when configuring Next.js applications, managing environment-specific settings, or deploying to Vercel/Railway/Heroku.