'node' 검색 결과

Run Hugging Face models in JavaScript or TypeScript with Transformers.js in Node.js or the browser.

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Converts TypeScript to idiomatic Dart 3 code, covering syntax mapping, type system translation, async patterns, and module migration. Activates when translating TypeScript interfaces, classes, enums, generics, union types, async/await patterns, or modules to Dart; migrating frontend or Node.js logic to Flutter/Dart; converting RxJS Observables to Dart Streams; adapting TypeScript utility types to Dart equivalents; or producing idiomatic Dart 3 output (sealed classes, records, pattern matching) from TypeScript source.

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Use the local MCP gateway and the per-app MCP picks. Use when the human asks to check, start, enable or disable the gateway, adopt other MCP servers behind it, wonder why an MCP server is direct or shared, or hit an After Effects MCP that will not start (Node >= 24).

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Universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development.

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Modern JavaScript/TypeScript development with Bun runtime. Covers package management, bundling, testing, and migration from Node.js. Use when working with Bun, optimizing JS/TS development speed, o...

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Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.

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BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript applications. Use when: bullmq, bull queue, redis queue, background job, job queue.

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Opinionated backend development standards for Node.js + Express + TypeScript microservices. Covers layered architecture, BaseController pattern, dependency injection, Prisma repositories, Zod valid...

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Instrument applications with Azure Monitor and OpenTelemetry for JavaScript (@azure/monitor-opentelemetry). Use when adding distributed tracing, metrics, and logs to Node.js applications with Appli...

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Azure Batch SDK for Java. Run large-scale parallel and HPC batch jobs with pools, jobs, tasks, and compute nodes.

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Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js ...

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Exhaustive idea extraction through recursive breadth-before-depth exploration with Deep Think protocol and fractal structure. Use during /ideate to transform raw ideas into comprehensive, structured ideation output. Writes to a fractal folder hierarchy — every node has an index, CX file, and children.

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Implement centralized audit logging and SIEM integration. Configure log retention and security monitoring. Use when implementing audit trail requirements.

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Use when generating cloud architecture diagrams as code — creating, modifying, or reviewing infrastructure diagrams using the Python Diagrams library. Covers AWS, Azure, GCP, Kubernetes, on-premises, and SaaS provider nodes. Generates PNG/SVG architecture diagrams from Python code with Graphviz rendering.

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Use when working with Coreweave — coreWeave GPU cloud management covering Kubernetes namespace inventory, GPU workload status, virtual server instances, persistent volume claims, node allocation, billing analysis, and network configuration. Use for comprehensive CoreWeave infrastructure assessment and GPU workload optimization.

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Use when working with Caprover — capRover self-hosted PaaS management covering app inventory, container status, custom domain mappings, persistent directory mounts, environment variable auditing, cluster node status, Docker registry integration, and Nginx configuration review. Use for managing CapRover infrastructure.

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Use when working with Aerospike — aerospike cluster management, namespace utilization, set analysis, and secondary index monitoring. Covers node health, storage engine statistics, migration tracking, UDF management, and XDR cross-datacenter replication status. Read this skill before any Aerospike operations.

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Use when working with Gcp Gke — google Kubernetes Engine cluster operations, node pool management, workload analysis, autopilot configuration, and upgrade planning via gcloud CLI.

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Use when working with Gcp Idle Resources — detect unused and idle GCP resources that incur cost without providing value. Covers unattached Persistent Disks, unused external IPs, stopped VMs, idle Cloud NAT, idle load balancers, old snapshots, idle Cloud SQL instances, abandoned GKE node pools, unused VPC connectors, and orphaned Filestore instances. Includes estimated monthly waste per resource and anti-hallucination rules for safe detection.

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Use when working with Azure Aks — azure Kubernetes Service (AKS) cluster management, node pool status, addon management, upgrade planning, and health diagnostics via Azure CLI.

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Analyze Compute Engine VM, Cloud SQL, Persistent Disk, and serverless (Cloud Functions/Cloud Run) utilization to identify right-sizing opportunities. Uses Cloud Monitoring metrics with anti-hallucination rules for E2 shared-core instances, sole-tenant nodes, preemptible/spot VMs, SUD eligibility, peak vs average analysis, CUD-aware savings, and estimated monthly savings calculations.

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Use when working with Aws Elasticache Deep — aWS ElastiCache deep analysis for Redis and Memcached clusters, replication health, failover analysis, and performance metrics. Covers node-level metrics, memory utilization, cache hit rates, eviction tracking, connection analysis, and engine-specific diagnostics.

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Use when working with Cassandra — apache Cassandra keyspace analysis, compaction strategies, repair status, nodetool operations, and cluster health monitoring.

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Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in browsers and server-side runtimes (Node.js, Bun, Deno) with WebGPU/WASM using pre-trained models from Hugging Face Hub.

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