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Found 1,182 Skills
Build production-ready AI workflows using Firebase Genkit. Use when creating flows, tool-calling agents, RAG pipelines, multi-agent systems, or deploying AI to Firebase/Cloud Run. Supports TypeScript, Go, and Python with Gemini, OpenAI, Anthropic, Ollama, and Vertex AI plugins.
Helps create, configure, and deploy Azure Static Web Apps using the SWA CLI. Use when deploying static sites to Azure, setting up SWA local development, configuring staticwebapp.config.json, adding Azure Functions APIs to SWA, or setting up GitHub Actions CI/CD for Static Web Apps.
Skill converted from mcp-deploy-manage-agents.prompt.md
This skill should be used when the user asks about service status, wants to rename a service, change service icons, link services, or create services with Docker images. For creating services with local code, prefer the `new` skill. For GitHub repo sources, use `new` skill to create empty service then `environment` skill to configure source.
This skill should be used when the user asks about Railway features, how Railway works, or shares a docs.railway.com URL. Fetches up-to-date Railway docs to answer accurately.
Deploy and manage projects on Vercel using token-based authentication. Use when working with Vercel CLI using access tokens rather than interactive login — e.g. "deploy to vercel", "set up vercel", "add environment variables to vercel".
Push local files to a Google Apps Script project.
Skill for working with Firebase Hosting (Classic). Use this when you want to deploy static web apps, Single Page Apps (SPAs), or simple microservices. Do NOT use for Firebase App Hosting.
Build and deploy Firebase Data Connect backends with PostgreSQL. Use for schema design, GraphQL queries/mutations, authorization, and SDK generation for web, Android, iOS, and Flutter apps.
Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices.
Build applications with InsForge Backend-as-a-Service. Use when developers need to: (1) Set up backend infrastructure (create tables, storage buckets, deploy functions, configure auth/AI) (2) Integrate InsForge SDK into frontend applications (database CRUD, auth flows, file uploads, AI operations, real-time messaging) (3) Deploy frontend applications to InsForge hosting IMPORTANT: Before any backend work, you MUST have the user's Project URL and API Key. If not provided, ask the user first. Key distinction: Backend configuration uses HTTP API calls to the InsForge project URL. Client integration uses the @insforge/sdk in application code.
Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.