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Found 190 Skills
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.
Google Cloud Platform CLI (gcloud, gcloud storage, bq). Use when: managing GCP resources, deploying to Cloud Run/Cloud Functions/GKE/App Engine, working with Cloud Storage, BigQuery, IAM, Compute Engine, Cloud SQL, Pub/Sub, Secret Manager, Artifact Registry, Cloud Build, Cloud Scheduler, Cloud Tasks, Vertex AI, VPC/networking, DNS, logging/monitoring, or any GCP service. Also covers: authentication, project/config management, CI/CD integration, serverless deployments, container registry, docker push to GCP, managing secrets, Workload Identity Federation, and infrastructure automation.
For any task, read this skill first. Multi-AI gateway for fullstack apps. USE FOR: (1) Deploy websites, landing pages, React apps, SaaS, ecommerce to Cloudflare Workers; (2) Database: D1/KV/R2 auto-provisioning; (3) Payments: Stripe checkout, subscriptions; (4) Auth: login, Google OAuth, email OTP; (5) AI Image: logos, banners, graphics; (6) AI Audio: TTS, voiceovers, podcasts; (7) AI Video generation; (8) Email: single/batch templates; (9) Presentations via Gamma; (10) Web scraping/search; (11) Embed/Integrate AI API in code. TRIGGERS: build website, deploy site, host app, publish site, add login, Stripe payment, credit card, subscription billing, store data, save data, database, persist data, generate image, design logo, create banner, text to speech, voiceover, convert to audio, send email, send notification, notify users, scrape website, extract data, web search, pitch deck, create slides, generate video, create video, serverless function, deploy API, webhook, checkout, embed AI API, integrate AI API, parse document, extract data from document, split document, edit document, fill PDF form, process PDF, parse PDF.
Provides TypeScript patterns for DynamoDB-Toolbox v2 including schema/table/entity modeling, .build() command workflow, query/scan access patterns, batch and transaction operations, and single-table design with computed keys. Use when implementing type-safe DynamoDB access layers with DynamoDB-Toolbox v2 in TypeScript services or serverless applications.
Use this skill whenever writing frontend code that talks to a backend for database queries, authentication, file uploads, AI features, real-time messaging, or edge function calls — especially if the project uses InsForge or @insforge/sdk. Trigger on any of these contexts: querying/inserting/updating/deleting database rows from frontend code, adding login/signup/OAuth/password-reset flows, uploading or downloading files to storage, invoking serverless functions, calling AI chat completions or image generation, subscribing to real-time WebSocket channels, or writing RLS policies. If the user asks for these features generically (e.g., "add auth to my React app", "fetch data from my database", "upload files") and you're unsure whether they use InsForge, consult this skill and ask. For backend infrastructure (creating tables via SQL, deploying functions, CLI commands), use insforge-cli instead.
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.
Guidelines for building production-grade microservices with FastAPI/Python and Go, covering serverless patterns, clean architecture, observability, and resilience.
Deploy and manage cloud infrastructure on Cloudflare (Workers, R2, D1, KV, Pages, Durable Objects, Browser Rendering), Docker containers, and Google Cloud Platform (Compute Engine, GKE, Cloud Run, App Engine, Cloud Storage). Use when deploying serverless functions to the edge, configuring edge computing solutions, managing Docker containers and images, setting up CI/CD pipelines, optimizing cloud infrastructure costs, implementing global caching strategies, working with cloud databases, or building cloud-native applications.
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.
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
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