Skill UI

Guides GCP users through GCS bucket configuration, offering best practices, configuration patterns, and production-ready snippets whenever someone asks about storage setup within Google Cloud.

Provides automated guidance for Google Cloud Storage lifecycle policy scenarios, including pattern recommendations, production-ready configurations, and best practices for compute, storage, BigQuery, Vertex AI, and other GCP-specific services.

Validates Vertex AI Agent Engine GitHub Actions workflows, enforcing Workload Identity Federation, least-privilege IAM, OIDC permissions, and security scanning so GCP deployments stay automated and secure.

Master Google Cloud’s Agent Development Kit and Starter Pack to build containerized multi-agent systems, automate RAG workflows, and deploy production-ready agents via Cloud Run, GKE, Agent Engine, or CI/CD pipelines.

Automates Google Cloud Vision workflows by discovering tools, managing the Composio Rube MCP connection, and executing schema-compliant operations via RUBE_MULTI_EXECUTE_TOOL.

This comprehensive guide details the end-to-end setup for Granola AI, an advanced AI meeting note-taking solution. It covers initial installation on macOS/Windows, authenticating with major cloud services (Google/Microsoft), and critically, granting all necessary system permissions (Screen Recording, Microphone) to ensure seamless, background audio capture and transcription. Use this guide when setting up Granola for the first time or troubleshooting connectivity issues.

Comprehensive guide for deploying applications powered by the Groq inference API. Covers best practices and specific setup instructions for multiple production environments, including Vercel Edge Functions, Google Cloud Run, Docker containers, and other containerized platforms. Essential for setting up robust, low-latency, production-ready AI services.

Automates Google Cloud IAM binding tasks by guiding users through best practices, generating production-ready code and configs, and validating outputs across compute, storage, BigQuery, Vertex AI, Cloud Run, Firebase, and other GCP services whenever iam binding creator is mentioned.

This comprehensive guide provides a multi-platform deployment solution for Ideogram-powered image generation APIs. It includes detailed code and setup steps for Vercel, Google Cloud Run, and self-hosted Docker containers. The solution addresses key production concerns, including secure secret management (API keys), handling generation timeouts, and ensuring generated images are persisted to durable cloud storage (like S3) with CDN integration for reliable service operation. Use this when migrating Ideogram prototypes to a production environment.

This skill guide provides comprehensive instructions for deploying Instantly.ai's API v2 webhook receivers and automation services to major cloud platforms. It covers setting up resilient, public HTTPS endpoints using Vercel serverless functions, Google Cloud Run containers, or Fly.io services. Use this when moving from local development to production or setting up robust webhook endpoints that handle real-time event processing.

This skill addresses the challenge of handling temporary CDN links for videos generated by Kling AI. It provides a comprehensive, multi-cloud solution to download the video asset and persistently upload it to major cloud storage platforms, including AWS S3, Google Cloud Storage (GCS), and Azure Blob Storage. It facilitates building robust, long-term media pipelines and ensures metadata preservation.

This skill provides a comprehensive guide for deploying LangChain chains and agents into production-grade APIs. It supports multiple development stacks, including Python (LangServe/FastAPI) and Node.js (Express). Topics covered include containerization using Docker, setting up robust health checks, and deploying to major cloud platforms like Google Cloud Run and AWS Lambda. Learn how to build scalable, observable, and enterprise-grade API endpoints for advanced LLM applications.