Skill UI

This comprehensive skill covers the full scope of Firebase services, including Authentication, Firestore, Cloud Functions, and Hosting. It goes beyond basic implementation, focusing on critical architectural principles: adopting a query-first, denormalized NoSQL mindset. Key insights include mandatory security rule design, optimal data modeling for performance, and correctly utilizing modular SDKs to build scalable and secure backends.

Scans Android APKs for Firebase misconfigurations, testing databases, storage, authentication, and cloud functions to surface vulnerabilities during mobile security audits.

This skill guides the end-to-end development, deployment, and secure integration of complex AI features into Firebase applications. It covers setting up Cloud Functions, Firestore/Storage rules, Authentication, and connecting robustly with Vertex AI/Gemini for advanced AI capabilities. Focuses on building production-grade, highly secure, data-intensive AI systems.

A comprehensive guide for deploying web scraping applications powered by Firecrawl to various production environments. Covers Vercel serverless functions, Google Cloud Run, and self-hosted Docker setups. Learn how to configure platform-specific secrets, implement API routes, and handle asynchronous crawl results via webhooks for scalable, reliable production service.

A comprehensive guide for deploying Fireflies.ai integrations into production environments. This skill covers setting up the GraphQL client, implementing secure webhook receivers with signature verification, and managing multi-platform deployments across Vercel, Docker, and Google Cloud Run. Ideal for integrating AI-powered meetings data into production services.

Manages Firebase/Firestore CRUD, queries, batch jobs, and security for applications while extending to A2A agent messaging, MCP server integration, and Cloud Run coordination for advanced workflows.

A comprehensive guide for deploying applications, especially those integrated with AI services like Gamma, to major cloud environments including Vercel, AWS, GCP, and GitHub. Covers best practices for secret management, environment variable configuration, and setting up CI/CD pipelines across various cloud architectures.

Guides building production-ready serverless apps on GCP with Cloud Run services and Functions, covering containerized APIs, event-driven Pub/Sub workflows, cold-start tuning, and deployment automation.

Generates complete, production-ready Google Cloud Platform (GCP) code examples and infrastructure templates. It spans various modern AI patterns, including ADK agents, Genkit RAG flows, and multimodal analysis using Vertex AI and Gemini. The output includes runnable code, deployment configuration (Terraform/IaC), security best practices (IAM, VPC-SC), and monitoring setup, ensuring enterprise-grade reliability and cost optimization.

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.

Generates production-ready Terraform, CloudFormation, Pulumi, ARM, or CDK templates via the infrastructure-as-code-generator plugin to automate cloud infrastructure deployment across AWS, Azure, and GCP from user specifications.