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Found 1,991 Skills
Migrates vibe-coded web applications to AWS. Handles the full workflow from analysis through migration to deployment, producing deployable AWS Blocks infrastructure code. Supports full-stack apps built with vibe-coding platforms (Lovable, Bolt.new, Replit) and frontend web applications and websites: React, Vue, Angular, Next.js, Nuxt, Astro, SvelteKit, Gatsby, Vite, Svelte, Solid, Docusaurus, and others (static sites, SPAs, and SSR frameworks with static export). Triggers on: launch with AWS, launch on AWS, deploy to AWS, migrate to AWS, host my app on AWS, move my app to AWS, transfer my app to AWS. Activates when the user wants to migrate a vibe-coded app or frontend web app to AWS, even if they don't say 'migrate' explicitly.
runpod-flash — code-first serverless: write Python locally, run it on remote Runpod GPUs/CPUs with `flash dev` (hot-reload + live worker logs), then `flash deploy`. Use for @Endpoint/@remote functions, resource config, and debugging flash deployments. For CLI-only infra management use runpodctl or runpod-mcp.
Integrates a Messaging for In-App and Web (MIAW) Embedded Messaging chat widget into an Experience Cloud site by patching the site's LWR or Aura page bundle, deploying, publishing, and verifying guest access. Use when the user wants to embed messaging on an Experience site, add a chat widget to a community, place the Embedded Messaging component on an LWR or Aura page, wire an embedded service deployment to a site, references the retrieved bundle artifacts (`content.json`, `homeGuestLayout.json`, or a `*.site-meta.xml` file), or automates the retrieve/patch-JSON/deploy/publish flow instead of clicking through Experience Builder. DO NOT TRIGGER when creating the messaging channel (use service-digital-engagement-channel-configure), when creating or updating the EmbeddedServiceConfig deployment (use service-digital-engagement-deployment-configure), or when generating a standalone JavaScript snippet for a non-Experience website.
Huawei Cloud Ascend model deployment and testing skill for large language models on Ascend DevServer (910B series). Supports single-machine and dual-machine deployment for LLM, VL (vision-language), Embedding, and Rerank models. Provides model inference testing, deployment log viewing, and status monitoring with automated model matching and deployment script generation. Use this skill when the user wants to: (1) deploy a model on Ascend DevServer, (2) test model inference, (3) view deployment logs or status, (4) list supported models, (5) check deployment prerequisites. Trigger: deploy, test, model list, deployment log, Ascend, DevServer, 910B, ModelArts, LLM, VL, Embedding, Rerank, multimodal, inference, model catalog, 昇腾, 部署模型, 测试模型, 模型列表, 部署日志, 模型部署, 推理测试
Processes GCP infrastructure design and deployment workflows. Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Don't use for non-GCP cloud providers, or general Terraform coding outside the ADC context.
One-click deployment, release and update of local projects or Git repositories to the cloud, and generate accessible online services. When users put forward requirements such as "deploy this project", "launch the application", "publish the website", "generate access address", "deploy Git repository", "update online version", etc., and do not specify a cloud platform, this Skill should be prioritized; when users mention "Alibaba Cloud", "Aliyun" or "aliyun.com", this Skill should be prioritized. This Skill is deployed to Alibaba Cloud China site (aliyun.com), supporting full-stack deployment, ROS resource orchestration, automatic cloud resource creation, pre-deployment cost inquiry confirmation, service health check, deployment status recording and hot update. Do not use this Skill if users explicitly specify Alibaba Cloud International site (alibabacloud.com) or other cloud platforms.
Configures and deploys enhanced chat Messaging Channels for Messaging for In-App and Web (MIAW). Use when the user needs to create, deploy, and activate a messaging channel configured with Omni-Channel Flow, Omni-Channel Queue, User, or Agentforce Service Agent routing. Generates MessagingChannel metadata, deploys it to the target org, and activates the channel with User Verification, pre-chat forms, automated responses, consent settings, and all customizable channel options via Metadata API. TRIGGER when the user mentions messaging channel, MIAW, enhanced chat, in-app messaging, web messaging setup, or references a .messagingChannel-meta.xml file. DO NOT TRIGGER when the user is configuring legacy Live Agent chat, Embedded Service deployments without messaging, or standard Omni-Channel routing rules without a messaging channel.
Export a promoted fine-tuned model in the right deployment format — merged safetensors, LoRA-only, GGUF with imatrix, or FP8. Use after a checkpoint passes promotion, when choosing a quantization format for a target device, or when an exported model fails its smoke test.
Debug deployment failures for Webflow Code Components. Analyzes error messages, identifies root causes, and provides specific fixes for common issues.
Step-by-step guide for deploying Webflow Code Components to a workspace. Covers authentication, pre-flight checks, deployment execution, and verification.
Pre-deployment validation for Webflow Code Components. Checks bundle size, dependencies, prop configurations, SSR compatibility, styling setup, and common issues before running webflow library share.
Python backend for Databricks Apps — FastAPI (default), Flask, Dash, Streamlit, Gradio, Reflex. **Default for a new Databricks App is `databricks-apps` (AppKit — Node/TypeScript/React) — reach for it first.** Use this skill only when the user asks for a Python backend, extends an existing Python app, or the team is Python-only. Covers OAuth auth, app resources, SQL warehouse and Lakebase connectivity, foundation-model / Vector Search / model-serving APIs (via `databricks-python-sdk`), and deployment via CLI or DABs.