Skill UI

Expert in developing complete, high-performance firmware and peripheral drivers for ARM Cortex-M platforms (STM32, Teensy, nRF52). Specializes in low-level hardware interaction, including implementing drivers for I²C, SPI, UART, and managing complex concurrency patterns using FreeRTOS/Zephyr. Provides critical guidance on optimizing for determinism, cache coherency, DMA transfers, and memory barriers to ensure reliable embedded system operation.

This skill provides comprehensive guidance and established patterns for managing and maintaining Windows 11 operating systems. It is designed to assist users in performing routine system updates, troubleshooting issues, and general system administration tasks within a Windows 11 environment, ensuring system stability and optimal performance.

Provides expert guidance on designing, securing, and optimizing cloud-native network infrastructures across AWS, Azure, and GCP, covering load balancing, service mesh, monitoring, and automation best practices for high-performance, resilient deployments.

A comprehensive skill guide for senior PostgreSQL administrators. It covers deep expertise in performance tuning using EXPLAIN ANALYZE, implementing advanced indexing strategies (GIN, GiST), setting up high availability via streaming or logical replication, and maintaining database health through VACUUM and pg_stat monitoring. Essential for optimizing complex, production-grade, and mission-critical database workloads.

This advanced workflow automates the process of analyzing the operational health of specific Azure resources. It ingests and analyzes raw logs, telemetry data, and performance metrics from diverse Azure services (e.g., VMs, Web Apps, Databases). The system performs comprehensive root cause analysis, classifies issues (Critical, High, Medium), and generates actionable, step-by-step remediation plans, significantly reducing manual troubleshooting time.

A comprehensive guide for optimizing query latency in Qdrant. This resource explains advanced performance tuning techniques, focusing on critical resource management like RAM utilization, segment count adjustments, and HNSW parameter tuning. It details strategies for scaling, quantization, and hardware considerations (e.g., local NVMe) to ensure consistently low-latency search performance, and outlines common pitfalls to avoid.

A comprehensive guide for diagnosing production performance issues in Qdrant vector databases. Learn how to systematically check the optimizer status, analyze high memory usage (OOM crashes), and troubleshoot slow query latencies using key metrics and dedicated API endpoints. Essential for maintaining optimal operational health.

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.