Skill UI

This skill analyzes Azure resource groups in depth, identifying all resources, their configurations, and complex interdependencies. It maps relationships—including network connections, data flows, and managed identities—to generate comprehensive, detailed Mermaid architecture diagrams. Use this when you need a clear, structured visualization and full documentation of an Azure environment's topology.

Generates HTML5 Canvas-based breadboard mockups and diagrams for retro computing builds, showing component placement, wiring, and labeled 6502/555 timer layouts as visual references or teaching aids.

This guide provides comprehensive best practices for creating optimized, secure, and efficient multi-stage Dockerfiles. Learn how to separate build environments (builder stage) from minimal runtime environments, significantly reducing image size and attack surface. Topics covered include layer caching optimization, security hardening (non-root users), and using minimal base images for reproducible builds.

This guide details the operational workflow for namespace-scoped tenants within KubeSphere DevOps. It outlines how users without cluster-admin privileges can securely perform DevOps operations by strictly utilizing KubeSphere's dedicated APIs (`/kapis/`) and authenticating via OAuth tokens, ensuring strict resource isolation and access control within their designated namespace.

KubeSphere Core acts as the central operating system for cloud-native application management built on Kubernetes. It provides essential functions, including API aggregation, multi-cluster routing, and multi-tenant separation. It manages core resources and simplifies complex cloud-native deployment and operation tasks.

WizTelemetry Platform Service is the core backend service for KubeSphere's WizTelemetry Observability Platform. It unifies common APIs and provides centralized platform services for collecting, managing, and analyzing multiple types of observability data, including Logging, Auditing, Event Streaming, Tracing, and Notifications. Use this service when setting up or configuring the foundational monitoring layer for a comprehensive, global observability solution within a Kubernetes environment.

WizTelemetry Logging is a comprehensive extension component within the KubeSphere Observability Platform. It provides robust capabilities for collecting, processing, and storing logs from container environments (stdout/stderr) and local disk files. Designed for system monitoring, it integrates with OpenSearch and supports advanced features like log query APIs, making it essential for maintaining system visibility and debugging in Kubernetes clusters.

Submit and manage autonomous lab protocols on Ginkgo Cloud Lab, leveraging RACs for cell-free protein expression validation/optimization, fluorescent pixel art, EstiMate AI assessments, and guided ordering of sample inputs through the web interface.

Guides medical device teams through preparing ISO 13485:2016 Quality Management System documentation by combining gap analysis, requirements references, templates, and step-by-step creation workflows for manuals, procedures, and compliance artifacts.

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 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.