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Found 1,319 Skills
Generate detailed layered architecture diagrams as self-contained HTML artifacts with inline SVG icons, CSS Grid nested container layout, SVG path connection overlays, and color-coded connection legends. Use when the user asks to create architecture diagrams, infrastructure diagrams, system topology diagrams, network diagrams, cloud architecture visuals, deployment diagrams, integration flow diagrams, or any request involving visual representation of system components, their containment hierarchy, and interconnections. Triggers on terms like "architecture diagram", "infra diagram", "system diagram", "topology", "deployment diagram", "network diagram", "integration architecture", or when the user provides a system description and asks for a visual/diagram.
Implements zero-downtime deployments on GKE using rolling updates, blue-green strategies, and health checks. Use when deploying new versions, rolling back failed deployments, configuring Spring Boot health probes (liveness/readiness), managing rollout status, or implementing progressive rollout patterns. Includes automated health verification and rollback procedures.
Integration templates for FastAPI endpoints, Next.js UI components, and Supabase schemas for ML model deployment. Use when deploying ML models, creating inference APIs, building ML prediction UIs, designing ML database schemas, integrating trained models with applications, or when user mentions FastAPI ML endpoints, prediction forms, model serving, ML API deployment, inference integration, or production ML deployment.
Scaffolds a production-ready Next.js turborepo with TypeScript, Tailwind CSS, shadcn CLI, Blode UI components from ui.blode.co, blode-icons-react, Biome, Ultracite, and Vercel deployment. Use when creating a new Next.js app, bootstrapping a turborepo, scaffolding a web project, starting a new website, or asking "create a Next.js project."
Strategic AI thinking frameworks and mental models from Satya Nadella's perspective on platform shifts, AI deployment, and building successful AI products. Use when evaluating AI strategy decisions, assessing platform opportunities, thinking through AI product positioning, considering enterprise AI deployment challenges, evaluating talent and team capabilities, or needing frameworks for justifying AI investments in terms of economic surplus. Triggers on questions about AI platform strategy, change management for AI adoption, building AI scaffolding layers, evaluating AI opportunities, or thinking through AI's societal implications.
Expert React Native and Expo development skill for building cross-platform mobile apps. Use this skill when creating, debugging, or optimizing React Native projects - Expo setup, native modules, navigation (React Navigation, Expo Router), performance tuning (Hermes, FlatList, re-render prevention), OTA updates (EAS Update, CodePush), and bridging native iOS/Android code. Triggers on mobile app architecture, Expo config plugins, app store deployment, push notifications, and React Native CLI tasks.
Expert knowledge for Azure Blueprints development including troubleshooting, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when defining Azure Blueprints, mapping built-in compliance sets, automating via CLI/PowerShell/REST, or fixing assignment errors, and other Azure Blueprints related development tasks. Not for Azure Policy (use azure-policy), Azure Resource Manager (use azure-resource-manager), Azure Managed Applications (use azure-managed-applications), Azure Deployment Environments (use azure-deployment-environments).
Expert knowledge for Azure Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Azure ML pipelines, AutoML, managed online/batch endpoints, prompt flow, or MLflow deployments, and other Azure Machine Learning related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure HDInsight (use azure-hdinsight), Azure Data Science Virtual Machines (use azure-data-science-vm).
Expert knowledge for Azure AI Custom Vision development including best practices, decision making, limits & quotas, security, integrations & coding patterns, and deployment. Use when exporting Custom Vision models, calling prediction APIs, using ONNX/TensorFlow, managing CMK/RBAC, or Smart Labeler, and other Azure AI Custom Vision related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI services (use microsoft-foundry-tools), Azure Machine Learning (use azure-machine-learning), Azure AI Foundry Local (use microsoft-foundry-local).
Write high-quality Rust unit tests following best practices. Use when writing new tests, reviewing test code, or improving test quality. Emphasizes clear naming, AAA pattern, isolation, and deployment confidence.
Guides Qdrant deployment selection. Use when someone asks 'how to deploy Qdrant', 'Docker vs Cloud', 'local mode', 'embedded Qdrant', 'Qdrant EDGE', 'which deployment option', 'self-hosted vs cloud', or 'need lowest latency deployment'. Also use when choosing between deployment types for a new project.
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for AI-agent, prompt-injection, MCP or toolchain, cloud, container, CI/CD, and supply-chain challenges. Use when the user asks to analyze prompt-to-tool flows, retrieval poisoning, mounted secrets, deployment drift, runtime-vs-manifest mismatches, registry provenance, or CI-produced artifacts under sandbox assumptions. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.