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Found 277 Skills
Use this skill whenever the user needs backend infrastructure management — creating database tables, running SQL, deploying serverless functions, managing storage buckets, deploying frontend apps, adding secrets, setting up cron jobs, checking logs, or running backend diagnostics — especially if the project uses InsForge. Trigger on any of these contexts: creating or altering database tables/schemas, writing RLS policies via SQL, deploying or invoking edge functions, creating storage buckets, deploying frontends to hosting, managing secrets/env vars, setting up scheduled tasks/cron, viewing backend logs, diagnosing backend health or performance issues, or exporting/importing database backups. If the user asks for these operations generically (e.g., "create a users table", "deploy my app", "set up a cron job", "check backend health") and you're unsure whether they use InsForge, consult this skill and ask. For writing frontend application code with the InsForge SDK (@insforge/sdk), use the insforge skill instead.
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.
Use when designing cloud architectures, planning migrations, or optimizing multi-cloud deployments. Invoke for Well-Architected Framework, cost optimization, disaster recovery, landing zones, security architecture, serverless design.
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
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
Use this skill when building MCP (Model Context Protocol) servers with TypeScript on Cloudflare Workers. This skill provides production-tested patterns for implementing tools, resources, and prompts using the official @modelcontextprotocol/sdk. It prevents 10+ common errors including export syntax issues, schema validation failures, memory leaks from unclosed transports, CORS misconfigurations, and authentication vulnerabilities. This skill should be used when developers need stateless MCP servers for API integrations, external tool exposure, or serverless edge deployments. For stateful agents with WebSockets and persistent storage, consider the Cloudflare Agents SDK instead. Supports multiple authentication methods (API keys, OAuth, Zero Trust), Cloudflare service integrations (D1, KV, R2, Vectorize), and comprehensive testing strategies. Production tested with token savings of ~70% vs manual implementation. Keywords: mcp, model context protocol, typescript mcp, cloudflare workers mcp, mcp server, mcp tools, mcp resources, mcp sdk, @modelcontextprotocol/sdk, hono mcp, streamablehttpservertransport, mcp authentication, mcp cloudflare, edge mcp server, serverless mcp, typescript mcp server, mcp api, llm tools, ai tools, cloudflare d1 mcp, cloudflare kv mcp, mcp testing, mcp deployment, wrangler mcp, export syntax error, schema validation error, memory leak mcp, cors mcp, rate limiting mcp
Deploy to Cloudflare edge platform. Use when deploying static sites to Pages, serverless functions to Workers, or configuring CDN/DNS. Covers Wrangler CLI.
Expert guidance on image optimization for web performance. Use when working with image formats (WebP, AVIF, JPEG, PNG, GIF, SVG, HEIC, JPEG XL), compression settings, responsive images, lazy loading, CDNs, Core Web Vitals, or any image-related web development task. Covers format selection, quality settings, srcset/sizes, picture element, art direction, fetchpriority, placeholder strategies (LQIP, blur-up, blurhash), container queries, HDR/wide color gamut, AI-powered image tools, edge/serverless processing, and performance optimization.
Guide development on EdgeOne Pages — Edge Functions, Node Functions, Middleware, and local dev workflows. Use when the user wants to create APIs, serverless functions, middleware, WebSocket endpoints, or full-stack features on EdgeOne Pages — e.g. "create an API", "add a serverless function", "write middleware", "build a full-stack app", "add WebSocket support", or "set up edge functions".
Optimize MongoDB client connection configuration (pools, timeouts, patterns) for Azure DocumentDB. Use this skill when working on functions that instantiate or configure a MongoDB client (e.g., calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing connection-related performance issues. Includes scenarios like building serverless functions, creating API endpoints, optimizing high-traffic applications, or debugging connection failures.
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.
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