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Found 1,972 Skills
Provides foundational knowledge about GuaraCloud PaaS platform — projects, services, deployments, tiers, build methods, and CLI installation and authentication. Use when the user mentions GuaraCloud, asks about platform concepts, or needs to set up the CLI.
Use this skill when users need to create, generate, modify, or validate Salesforce Lightning pages (FlexiPages). Trigger when users mention RecordPage, AppPage, HomePage, Lightning pages, page layouts, adding components to pages, or page customization. Also use when users say things like 'create a Lightning page', 'add a component to a page', 'customize the record page', 'generate a FlexiPage', or when they're working with FlexiPage XML files and need help with components, regions, or deployment errors. Always use this skill for any FlexiPage-related work, even if they just mention 'page' in the context of Salesforce.
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.
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.
Comprehensive guide for working with HashiCorp Terraform Stacks. Use when creating, modifying, or validating Terraform Stack configurations (.tfcomponent.hcl, .tfdeploy.hcl files), working with stack components and deployments from local modules, public registry, or private registry sources, managing multi-region or multi-environment infrastructure, or troubleshooting Terraform Stacks syntax and structure.
Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. Use when optimizing inference speed (1.5-3.6× speedup), reducing latency for real-time applications, or deploying models with limited compute. Covers draft models, tree-based attention, Jacobi iteration, parallel token generation, and production deployment strategies.
Deploy and manage web apps using Azure App Service with auto-scaling, deployment slots, SSL/TLS, and monitoring. Use for hosting web applications on Azure.
Infrastructure as Code using Terraform with modular components, state management, and multi-cloud deployments. Use for provisioning and managing cloud resources.
Expert in building scalable ML systems, from data pipelines and model training to production deployment and monitoring.
Container orchestration with Docker Compose for multi-container applications, networking, volumes, and production deployment
Comprehensive Azure cloud expertise covering all major services (App Service, Functions, Container Apps, AKS, databases, storage, monitoring). Use when working with Azure infrastructure, deployments, troubleshooting, cost optimization, IaC (Bicep/ARM), CI/CD pipelines, or any Azure-related development tasks. Provides scripts, templates, and best practices for production-ready Azure solutions.
Deploy and configure applications on Vercel. Use when deploying Next.js apps, configuring serverless functions, setting up edge functions, or managing Vercel projects. Triggers on Vercel, deploy, serverless, edge function, Next.js deployment.