Skill UI

This comprehensive profiler provides systematic performance analysis for modern applications built with Node.js, Python, and Go. It detects critical bottlenecks across CPU, memory, and I/O dimensions. Key features include generating flamegraphs, analyzing bundle sizes, optimizing database queries (N+1 detection), and running rigorous load tests using k6 and Artillery. It mandates before-and-after measurements to ensure verifiable performance improvements.

This comprehensive skill analyzes Zeek conn.log and NetFlow data to proactively detect advanced indicators of ransomware activity. It identifies critical threats such as Command and Control (C2) beaconing patterns, connections to TOR exit nodes, large-scale data exfiltration flows, and suspicious DNS anomalies. It is essential for threat hunting and complex security incident response.

A specialized tool for performing comprehensive CIS Kubernetes Benchmark audits. It verifies the security configurations of control planes, worker nodes, and etcd against industry best practices. The output is designed to generate actionable compliance evidence for audits like SOC 2 or PCI DSS, helping users identify vulnerabilities, determine non-applicability on managed clusters (EKS, GKE, AKS), and plan remediation strategies.

Provides comprehensive guidance on determining the optimal scaling strategy for Qdrant vector databases. Covers when to transition from vertical to horizontal scaling, how to select the right number of nodes and shards, and best practices for setting replication factors to ensure zero-downtime operation and fault tolerance. Also details proper shard management and common scaling pitfalls to avoid.

A comprehensive guide to optimizing CAST AI's core performance metrics, including node provisioning speed, autoscaler responsiveness, and API call efficiency. This skill covers techniques like configuring headroom, selecting optimal instance families, tuning evictors, and implementing caching for multi-cluster dashboards to ensure high availability and cost efficiency in cloud environments.

This script generates a comprehensive diagnostic bundle for CAST AI deployed on a Kubernetes cluster. It automatically collects crucial data including component logs, pod statuses, Helm releases, node inventories, and cluster events into a single archive. Use this tool when preparing a detailed support ticket or performing deep technical troubleshooting.

This skill provides comprehensive API calls using `curl` to interact with the CAST AI platform. It allows users to list connected Kubernetes clusters, retrieve detailed cost savings reports, and inspect the inventory of managed nodes. It is essential for verifying connectivity, auditing cloud spending, and monitoring resource allocation after onboarding.

This runbook provides structured steps for responding to critical production incidents on the CoreWeave platform. Use it when dealing with GPU workload failures, inference service outages, or general Kubernetes resource issues. It guides users through checking pod status, node health, and diagnosing common model loading errors to ensure rapid service recovery.

A comprehensive solution for monitoring CoreWeave cluster events and GPU workload status using webhooks. It tracks critical lifecycle events such as pod readiness, job completion, volume attachment, and node health. Essential for building automated scaling, alerting, and recovery pipelines for large-scale GPU-accelerated inference and training workloads.

This guide provides a comprehensive strategy for configuring Klaviyo across development, staging, and production environments. It covers best practices for using separate API keys, implementing robust environment detection logic (like reading NODE_ENV), and utilizing secret management solutions (AWS/GCP/Vault). Crucially, it teaches how to implement 'guards' to prevent accidental real-world actions, such as sending live emails or deleting data, in non-production environments, ensuring data integrity and smooth CI/CD deployment.

This skill generates standardized, production-ready `mise.toml` configurations. It helps developers standardize runtime versions across mixed-language projects (e.g., Node.js, Python, Go, etc.) and CI/CD pipelines, eliminating the need for multiple legacy version managers like asdf or nvm. Ideal for ensuring reproducible, consistent development environments.

This utility publishes various Aegis-related events (such as person detection, alerts, and clip completion) to an MQTT broker. It is designed for seamless integration with smart home and automation platforms like Home Assistant or Node-RED, enabling real-time, event-driven monitoring and system linkage.