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Azure Resource Architecture Visualizer

azure-resource-visualizer

github/awesome-copilot

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.

Power Automate Flow Monitoring And Governance

flowstudio-power-automate-monitoring

github/awesome-copilot

Provides comprehensive, enterprise-level monitoring for all Power Automate flows across an entire tenant. Using a cached store, it tracks failure rates, run health trends, asset inventory (makers, apps, connections), and compliance reports without hitting API rate limits. Ideal for governance teams needing an aggregated view of platform health and root-cause analysis.

Legacy Circuit Mockups Visualizer

legacy-circuit-mockups

github/awesome-copilot

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.

Operating KubeSphere DevOps as a Tenant

kubesphere-devops-tenant

kubesphere/kubesphere

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.

Qdrant Scaling and Distribution Best Practices

qdrant-horizontal-scaling

github/awesome-copilot

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.

Optimizing Qdrant Query Latency

qdrant-minimize-latency

github/awesome-copilot

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.

Debugging Qdrant Performance Issues

qdrant-monitoring-debugging

github/awesome-copilot

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.

Upgrading Qdrant Versions Safely

qdrant-version-upgrade

github/awesome-copilot

Provides comprehensive guidance on upgrading your Qdrant vector database version while ensuring data integrity and maintaining application availability. It covers compatibility rules for major/minor versions, recommends step-by-step migration plans, and details how to perform zero-downtime rolling upgrades using replication factors.

Optimize CAST AI Performance and Efficiency

castai-performance-tuning

jeremylongshore/claude-code-plugins-plus-skills

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.

Security Best Practices For CAST AI

castai-security-basics

jeremylongshore/claude-code-plugins-plus-skills

This guide details securing the CAST AI integration across multiple layers. It covers best practices for API key management (including rotation and secrets storage), implementing least-privilege RBAC using 'kubectl', deploying the Kvisor security agent for runtime scanning, and setting up Kubernetes Network Policies to restrict egress traffic. Use this when hardening production clusters or performing security audits.

Upgrade And Migrate CAST AI Infrastructure

castai-upgrade-migration

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide detailing the systematic process for upgrading and migrating CAST AI components. This includes updating Helm charts (agent, controller, evictor) and Terraform providers. It outlines prerequisites, step-by-step upgrade procedures, validation checks, and necessary rollback procedures to ensure a safe transition between versions.

Figma API Incident Runbook

figma-incident-runbook

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive runbook for rapid incident response to Figma REST API failures. It guides users through quick triage (checking status, authentication, rate limits), decision-making based on error codes (403, 429, 500), applying immediate mitigation strategies (token rotation, fallback modes), and completing thorough postmortem documentation.

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