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Found 307 Skills
This skill provides comprehensive knowledge for integrating Vercel KV (Redis-compatible key-value storage powered by Upstash) into Vercel applications. It should be used when setting up Vercel KV for Next.js applications, implementing caching patterns, managing sessions, or handling rate limiting in edge and serverless functions. Use this skill when: - Setting up Vercel KV for Next.js applications - Implementing caching strategies (page cache, API cache, data cache) - Managing user sessions or authentication tokens in serverless environments - Building rate limiting for APIs or features - Storing temporary data with TTL (time-to-live) - Migrating from Cloudflare KV to Vercel KV - Encountering errors like "KV_REST_API_URL not set", "rate limit exceeded", or "JSON serialization errors" - Need Redis-compatible API with strong consistency (vs eventual consistency) Keywords: vercel kv, @vercel/kv, vercel redis, upstash vercel, kv vercel, redis vercel edge, key-value vercel, vercel cache, vercel sessions, vercel rate limit, redis upstash, kv storage, edge kv, serverless redis, vercel ttl, vercel expire, kv typescript, next.js kv, server actions kv, edge runtime kv
Deployment and hosting platform specialist covering Vercel, Railway, and Convex. Use when deploying applications, configuring edge functions, setting up continuous deployment, managing serverless infrastructure, containerized deployments, real-time backends, or choosing deployment platforms. Covers edge computing (Vercel), container orchestration (Railway), and reactive backends (Convex).
Guide users to manage Alibaba Cloud resources using the Aliyun CLI command-line tool. Covers CLI installation, credential configuration, plugin management, command construction, and error troubleshooting. Use this skill when the user wants to operate Alibaba Cloud services from the terminal — including ECS (云服务器, cloud servers), Function Compute (函数计算, serverless), RDS (云数据库, databases), OSS (对象存储, object storage), SLS (日志服务, log service), VPC (专有网络, networking), ESS (弹性伸缩, auto scaling), and any other Alibaba Cloud product. Also use when the user mentions "aliyun", "阿里云", "阿里云CLI", "命令行", asks about CLI plugin installation, encounters Aliyun CLI errors (InvalidAccessKeyId, SignatureDoesNotMatch, Throttling), or needs help constructing aliyun commands with correct parameter syntax.
Primary entry point for building, managing, and orchestrating data pipelines on Google Cloud. Guides users to the appropriate skill for dbt, Dataflow (Apache Beam), Dataform, Spark (Dataproc Serverless), BigQuery Data Transfer Service (DTS) or orchestration pipeline using Cloud Composer. Clarify requirements and resolve ambiguity for creating, updating and running data pipelines.
Expert AWS Cloud Advisor for architecture design, security review, and implementation guidance. Leverages AWS MCP tools for accurate, documentation-backed answers. Use when user asks about AWS architecture, security, service selection, migrations, troubleshooting, or learning AWS. Triggers on AWS, Lambda, S3, EC2, ECS, EKS, DynamoDB, RDS, CloudFormation, CDK, Terraform, Serverless, SAM, IAM, VPC, API Gateway, or any AWS service.
How to choose and configure data sources for MapLibre GL JS — rendering your own data without tiles, hosted tile services, serverless PMTiles, self-hosted tile servers, tile schemas, glyphs, and sprites.
Diagnose and manage Alibaba Cloud databases through natural language. Use when users need to troubleshoot database performance issues (high CPU, slow queries, abnormal connections, lock waits), check instance status, analyze disk space, optimize SQL, run health inspections, or detect security baseline violations. Supports RDS (MySQL/PostgreSQL/SQL Server), PolarDB, MongoDB, Redis (Tair), and Lindorm. Trigger this skill even for casual descriptions like "my database is slow", "can't connect to the database", "help me check this SQL", or "database disk is almost full". Also suitable for consulting Alibaba Cloud-specific database features (e.g., PolarDB Serverless, DAS autonomy capabilities) and comparing product differences (RDS vs PolarDB). Do NOT use this skill for general SQL tutorials, non-Alibaba Cloud databases, or local database administration.
Configure autoscaling for Kubernetes, VMs, and serverless workloads based on metrics, schedules, and custom indicators.
Set up Cloudflare Workers with Hono routing, Vite plugin, and Static Assets using production-tested patterns. Prevents 6 errors: export syntax, routing conflicts, HMR crashes, and Service Worker format confusion. Use when: creating Workers projects, configuring Hono or Vite for Workers, deploying with Wrangler, adding Static Assets with SPA fallback, or troubleshooting export syntax, API route conflicts, scheduled handlers, or HMR race conditions. Keywords: Cloudflare Workers, CF Workers, Hono, wrangler, Vite, Static Assets, @cloudflare/vite-plugin, wrangler.jsonc, ES Module, run_worker_first, SPA fallback, API routes, serverless, edge computing, "Cannot read properties of undefined", "Static Assets 404", "A hanging Promise was canceled", "Handler does not export", deployment fails, routing not working, HMR crashes
Optimize application performance - bundle size, API response times, database queries, React rendering, and serverless function performance. Use when investigating slow pages, profiling, load testing, or before production deployments.
Use this skill when developing Node.js backend services or CloudBase cloud functions (Express/Koa/NestJS, serverless, backend APIs) that need AI capabilities. Features text generation (generateText), streaming (streamText), AND image generation (generateImage) via @cloudbase/node-sdk ≥3.16.0. Built-in models include Hunyuan (hunyuan-2.0-instruct-20251111 recommended), DeepSeek (deepseek-v3.2 recommended), and hunyuan-image for images. This is the ONLY SDK that supports image generation. NOT for browser/Web apps (use ai-model-web) or WeChat Mini Program (use ai-model-wechat).
Complete knowledge domain for Cloudflare Workers AI - Run AI models on serverless GPUs across Cloudflare's global network. Use when: implementing AI inference on Workers, running LLM models, generating text/images with AI, configuring Workers AI bindings, implementing AI streaming, using AI Gateway, integrating with embeddings/RAG systems, or encountering "AI_ERROR", rate limit errors, model not found, token limit exceeded, or neurons exceeded errors. Keywords: workers ai, cloudflare ai, ai bindings, llm workers, @cf/meta/llama, workers ai models, ai inference, cloudflare llm, ai streaming, text generation ai, ai embeddings, image generation ai, workers ai rag, ai gateway, llama workers, flux image generation, stable diffusion workers, vision models ai, ai chat completion, AI_ERROR, rate limit ai, model not found, token limit exceeded, neurons exceeded, ai quota exceeded, streaming failed, model unavailable, workers ai hono, ai gateway workers, vercel ai sdk workers, openai compatible workers, workers ai vectorize