Skill UI

A comprehensive guide for deploying Apollo.io integrations to production environments. This skill covers robust deployment strategies across multiple cloud platforms, including Vercel, GCP Cloud Run, and Kubernetes. It emphasizes best practices such as implementing health check endpoints, managing secrets using dedicated secret managers, and structuring CI/CD pipelines for reliable, scalable, and secure production rollouts.

Automates database archival workflows by identifying historical records in PostgreSQL or MySQL, applying retention policies, and migrating data to archive tables or cold storage (S3/Azure Blob/GCS) with compression and compliance tracking.

Automates database archival workflows by identifying historical records in PostgreSQL or MySQL, applying retention policies, and migrating data to archive tables or cold storage (S3/Azure Blob/GCS) with compression and compliance tracking.

This SDK provides comprehensive content moderation capabilities for Python applications using Azure AI. It allows developers to analyze text and images to detect harmful content across multiple categories, including hate speech, violence, sexual content, and self-harm. Key features include multi-severity classification, managing custom blocklists, and analyzing content from local files or URLs. Ideal for pre-moderating user-generated content (UGC) or AI outputs to ensure platform safety.

This SDK provides comprehensive content moderation capabilities for Python applications using Azure AI. It allows developers to analyze text and images to detect harmful content across multiple categories, including hate speech, violence, sexual content, and self-harm. Key features include multi-severity classification, managing custom blocklists, and analyzing content from local files or URLs. Ideal for pre-moderating user-generated content (UGC) or AI outputs to ensure platform safety.

Automated GCP skill that activates when you ask about BigQuery ML model creator tasks, delivering best-practice guidance, production-ready code, and validation for compute, storage, BigQuery, Vertex AI, and other platform services.

Automates guidance for setting up and optimizing BigQuery scheduled queries within GCP, offering best practices, configuration templates, and validation for production-ready data workflows.

Automates BigQuery table creation by guiding GCP best practices, generating ready-to-deploy configurations, and validating resources whenever you trigger the BigQuery table creator skill.

Automates creating and validating GCP BigQuery views with best-practice guidance, production-ready code snippets, and integrations for Vertex AI, Cloud Run, Firebase, and similar services to keep analytics workloads consistent.

Cloud Architect Blueprint provides guidance for designing resilient AWS, Azure, and GCP topologies, planning secure migrations, tightening zero-trust controls, optimizing costs, and orchestrating disaster recovery across multi-region deployments.

A comprehensive workflow bundle covering the entire cloud-native development lifecycle. It guides users through critical phases, including cloud infrastructure setup (AWS, Azure, GCP, Terraform IaC), container orchestration with Kubernetes, robust CI/CD pipeline automation, observability implementation, security hardening, cost optimization, and disaster recovery planning. This ensures best practices across all stages of modern application deployment.

Automates guidance, code, and configuration for Google Cloud Function scenarios, helping engineers follow best practices for compute, storage, BigQuery, Vertex AI, and other GCP services.