Loading...
Loading...
Found 277 Skills
Deploy and manage Supabase Edge Functions. Use for invoking serverless functions, deploying new functions, and managing function deployments.
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.
Expert knowledge for Drizzle ORM - the lightweight, type-safe SQL ORM for edge and serverlessUse when "drizzle, drizzle orm, drizzle-kit, drizzle schema, drizzle migration, drizzle relations, sql orm typescript, edge database, d1 database, orm, database, typescript, sql, edge, serverless, d1, postgres, mysql, sqlite" mentioned.
Cloudflare Durable Objects stateful serverless playbook: DurableObjectState, Storage API (SQLite/KV), WebSocket hibernation, alarms, RPC, bindings, migrations, limits, pricing. Keywords: Durable Objects, DurableObjectState, DurableObjectStorage, SQLite, ctx.storage, WebSocket hibernation, acceptWebSocket, alarms, setAlarm, RPC, blockConcurrencyWhile.
This skill provides comprehensive knowledge for integrating Neon serverless Postgres and Vercel Postgres (which is built on Neon infrastructure) into web applications. It should be used when setting up serverless Postgres databases, configuring connection pooling for edge and serverless environments, implementing database branching workflows, or troubleshooting Postgres connection issues in Cloudflare Workers, Vercel Edge Functions, or Node.js serverless functions. Use this skill when: - Setting up Neon Postgres for Cloudflare Workers, Vercel Edge, or serverless environments - Configuring Vercel Postgres for Next.js applications - Implementing database branching workflows (git-like database branches) - Integrating Drizzle ORM or Prisma with Neon/Vercel Postgres - Debugging connection pool errors, transaction timeouts, or SSL configuration issues - Migrating from D1/SQLite to Postgres or from traditional Postgres to serverless Postgres - Setting up point-in-time restore (PITR) or database backups - Encountering errors like "connection pool exhausted", "TCP connections not supported in serverless", or "sslmode required" Keywords: neon postgres, @neondatabase/serverless, @vercel/postgres, serverless postgres, postgres edge, neon branching, vercel database, http postgres, websocket postgres, pooled connection, drizzle neon, prisma neon, postgres cloudflare, postgres vercel edge, sql template tag, neonctl, database branches, point in time restore, postgres migrations, serverless sql, edge database, neon api, vercel sql
Use when "designing AWS architecture", "serverless AWS", "cloud infrastructure", "Lambda", "DynamoDB", or asking about "AWS cost optimization", "CloudFormation", "CDK", "API Gateway", "ECS", "EKS"
Use when creating cloud sandboxes (microVMs) to run code, start dev servers, and generate live preview URLs. Also covers deploying AI agents, MCP servers, batch jobs, and Agent Drives (shared filesystems) on Blaxel's serverless infrastructure. Reach for this skill when you need isolated compute environments, real-time app previews, shared file storage across sandboxes, or to deploy agentic workloads.
Manages existing Elastic Cloud Serverless projects: list, get, update, delete, reset credentials, resume, and load saved credentials. Connects to existing projects by resolving endpoints and acquiring scoped Elasticsearch API keys. Use when performing day-2 operations on serverless projects, connecting to an existing project, loading or resetting project credentials, or looking up project details.
Generates a Jupyter notebook that deploys fine-tuned models from SageMaker Serverless Model Customization to SageMaker endpoints or Bedrock. Use when the user says "deploy my model", "create an endpoint", "make it available", or asks about deployment options. Identifies the correct deployment pathway (Nova vs OSS), generates deployment code, and handles endpoint configuration.
Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Manage serverless MySQL databases and branches on PlanetScale