Skill UI

This skill uses the OCI Usage API and SDK to programmatically track spending across compartments, services, and shapes. It allows users to query granular cost data, set detailed budget alerts (e.g., 80%, 95%, forecast), and identify cost optimization opportunities like utilizing Always Free tiers or preemptible instances, ensuring proactive and precise cloud cost management.

This skill allows users to programmatically set up a comprehensive observability stack for Oracle Cloud Infrastructure (OCI) resources. It guides the creation of metric queries, alarm rules, custom metric publishing, and detailed log searches using the Python SDK. By automating monitoring and alerting, users gain full control over their infrastructure visibility, eliminating reliance on the OCI Console UI for critical operational checks.

A comprehensive checklist designed to validate that an Oracle Cloud Infrastructure (OCI) environment meets rigorous production-grade standards. This tool automates checks for critical security controls, including compartment isolation, backup policy enforcement, NSG/security list auditing, API key rotation status, encryption verification, and compliance monitoring via Cloud Guard. Use it when preparing an OCI environment for mission-critical workloads or conducting a formal security audit.

Programmatically query Oracle Cloud Infrastructure (OCI) metrics using the Monitoring Query Language (MQL) and create monitoring alarms via the Python SDK. This skill bypasses the limitations of the OCI console query builder, allowing reliable retrieval of key infrastructure metrics such as CPU utilization, memory usage, network traffic, and disk I/O. Ideal for building robust dashboards, automating resource monitoring, and setting up complex alerting rules.

A comprehensive guide detailing how to establish robust monitoring for Qdrant. Covers setting up Prometheus metrics scraping, implementing Liveness and Readiness probes for Kubernetes, configuring alerts, and centralizing logs. It provides specific instructions for both self-hosted and Hybrid Cloud environments, ensuring full operational visibility and compliance.

This advanced skill automates the entire lifecycle of cloud infrastructure deployment. Instead of manual documentation review, it researches current best practices across multi-cloud platforms (AWS, GCP, Azure), synthesizes a coherent deployment strategy, and generates production-grade Infrastructure as Code (IaC). It outputs comprehensive artifacts, including Terraform modules, Kubernetes manifests, CI/CD pipelines, monitoring setups, and cost estimates, ensuring secure and optimized deployment.

Master event-driven patterns within Snowflake using native alerts, email integrations, external functions, and cloud notification services (S3/GCS). This skill is essential for building robust, reactive pipelines that trigger actions (like sending alerts, calling external APIs, or ingesting data) in response to data changes or specific system events. Use cases include data quality checks, real-time monitoring, and automated notifications.

A robust API-backed skill for fetching YouTube transcripts, searching video content, browsing channels, and extracting playlists. It functions reliably from any cloud server environment, bypassing limitations found in local tools like yt-dlp or reliance on Google API keys. Ideal for building research corpora, competitive intelligence monitoring, and systematic content analysis.

This framework provides comprehensive detection capabilities for compromised cloud credentials across major platforms including AWS, Azure, and GCP. It analyzes critical threat indicators such as anomalous API activity, impossible travel patterns (impossible login locations), and unauthorized resource provisioning. Designed for incident response, security monitoring, and building robust detection rules to mitigate account takeover and credential abuse.

This guide teaches security teams how to proactively detect and respond to unauthorized cryptocurrency mining operations across major cloud platforms (AWS, Azure). It utilizes a multi-layered approach by analyzing compute cost anomalies, monitoring GuardDuty findings, inspecting network traffic to known mining pools, and analyzing runtime process execution in EC2, ECS, and EKS environments.