「ops」の検索結果

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

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Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

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Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.

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Operate and maintain OpenViking server - configure, install, start, stop, and cleanup the server. Use when need to setup or manage OpenViking service deployment.

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Use when: User wants to extend Docker with custom tools, personalize the Docker environment, or set up user-specific Docker customization. Triggers: 'extend docker', 'docker-extend', 'add tools to docker', 'customize docker', 'add my tools to the container', 'personalize docker setup', 'docker user setup', 'install tools in docker'. Does: Interactively sets up Dockerfile.user and docker-compose.override.yml so users can add personal tools to their Docker environment without affecting maintainer files or committing user-specific config to git.

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Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus

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Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges

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Supermemory is a state-of-the-art memory and context infrastructure for AI agents. Use this skill when building applications that need persistent memory, user personalization, long-term context retention, or semantic search across knowledge bases. It provides Memory API for learned user context, User Profiles for static/dynamic facts, and RAG for semantic search. Perfect for chatbots, assistants, and knowledge-intensive applications.

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Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform

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Deploy your own Open-Inspect instance. Use when the user wants to set up, deploy, or onboard to Open-Inspect. Guides through repository setup, credential collection, Terraform deployment, and verification with user handoffs.

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Chinese-first internal-tool / ops dashboard template — light-mode Linear-grade layout with serif headlines, tabular Inter numerals, KPI hero, pulse bars, progress rings, team-presence grid, activity timeline, and CJK-aware typography.

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Dark-themed cloud-platform aesthetic with modular grids, glass-like panels, and strong data hierarchy for productivity dashboards.

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Start the Openrind Desktop dev stack via Docker and verify real user flows via Chrome MCP. Triggers when user mentions: - "dev-up.sh" - "docker dev stack" - "verify in chrome mcp" - "test the real flow"

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Issues, busca, comentários, tags, artigos e registro de trabalho no YouTrack Cloud via MCP oficial. Use quando o usuário disser "YouTrack", "criar issue", "minhas issues", "buscar tarefas", "comentar na issue", "atribuir para", "mudar o estado", "registrar horas", "artigo da knowledge base", ou citar um ID tipo PROJ-123. Boards e sprints são da skill youtrack-rest.

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Mantém a documentação técnica viva no Notion e no repositório — arquitetura, runbooks, inventário, ADRs e procedimentos operacionais, gerados a partir da infraestrutura real. Use quando o usuário disser "documentar", "runbook", "ADR", "wiki", "Notion", "atualizar a documentação", "inventário", "ninguém sabe como isso funciona".

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Infraestrutura para IA — GPU, servidores MCP, gateway de LLM, pipeline de inferência, custo de token, cache semântico e observabilidade de modelo. Use quando o usuário disser "GPU", "MCP server", "LLM", "inferência", "modelo", "gateway de IA", "custo de token", "rate limit da API de IA", "self-host de modelo".

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Arquitetura e diagnóstico AWS — VPC, EC2, ECS, EKS, ALB, NLB, RDS, ElastiCache, S3, CloudFront, Route53, IAM, WAF, GuardDuty. Use quando o usuário disser "AWS", "VPC", "ALB", "RDS", "revisar a arquitetura", "Well-Architected", "subnet", "security group", "IAM", ou citar qualquer serviço AWS. Leitura livre; qualquer mudança passa pelo portão de confirmação.

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Operação de aplicação Laravel em produção — Horizon, queue, scheduler, Octane, Redis, Supervisor, PHP-FPM, cache e deploy. Use quando o usuário disser "laravel", "horizon", "queue", "fila travada", "job falhando", "octane", "artisan", "php-fpm", "supervisor", "scheduler não roda".

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Dockerfile, multi-stage build, Compose, buildx, registry, otimização e segurança de imagem. Use quando o usuário disser "docker", "dockerfile", "imagem", "container", "build", "compose", "imagem muito grande", "trivy", "vulnerabilidade na imagem".

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Diagnóstico e operação de Kubernetes — pods, deployments, ingress, HPA, PVC, StorageClass, NetworkPolicy, Secrets, Helm, ArgoCD, cert-manager. Use quando o usuário disser "kubernetes", "k8s", "pod", "deployment", "ingress", "CrashLoopBackOff", "não sobe", "escalar", "helm", "argocd". Leitura livre; apply, scale, delete passam pelo portão.

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Métricas, logs, traces, dashboards, alertas e SLO — Prometheus, Grafana, Loki, Tempo, Mimir, Zabbix, Alertmanager. Use quando o usuário disser "dashboard", "alerta", "métrica", "PromQL", "Grafana", "SLO", "golden signals", "não temos visibilidade", "monitoramento".

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Estratégia de quality gates determinísticos e adoção incremental para CI/CD. Use quando o usuário pedir "quality gate", "gate de qualidade", "política de bloqueio", "baseline", "ratchet", "qualidade no CI" ou "SonarQube".

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Segurança de infraestrutura e pipeline — Trivy, Falco, CrowdSec, Fail2Ban, WAF, TLS, IAM, secrets, OWASP, Security Hub. Use quando o usuário disser "segurança", "vulnerabilidade", "CVE", "hardening", "WAF", "secrets", "exposto", "auditoria de segurança", "pentest".

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Deploy and optimize applications on Vercel with preview deployments, edge functions, environment variables, and performance monitoring. Use when deploying Next.js applications, setting up preview deployments per pull request, configuring environment variables, using Vercel Edge Functions, optimizing build performance, implementing redirects and rewrites, configuring custom domains, or monitoring application performance with Vercel Analytics.

日本語の概要は準備中です。原文の説明を表示しています。