prune
免费Systematically evaluate weak, stale, or low-conviction theses for upgrade, monitoring, or closure. Use when user says "prune", "kill list", "clean up theses", "what should I close", or "reduce portfolio".
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云、CI/CD、监控、部署(6826 个)
Systematically evaluate weak, stale, or low-conviction theses for upgrade, monitoring, or closure. Use when user says "prune", "kill list", "clean up theses", "what should I close", or "reduce portfolio".
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Extract point-scale CMIP6 historical and SSP future climate data from the Pangeo Google Cloud catalog and convert them into bias-corrected additive or multiplicative anomalies for LSM or EcoSIM climate forcing. Use when a task needs site latitude/longitude, scenario-specific CMIP6 variables, vapor pressure derived from huss and ps, calendar-aware day-of-year climatologies, or projected change summaries for the 2050s and 2090s.
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Read and analyze log entries from Cloud Logging using the gcloud CLI.
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Dockerベースのアプリケーションのデプロイメント手順書(Markdown)を作成するスキル。「デプロイ手順書」「デプロイメント手順」「deployment guide」「本番環境への配置手順」「サーバーへの配置手順」などの依頼でトリガーする。Docker Composeビルド→イメージ転送→サーバー配置→設定→動作確認→cron設定の流れで手順書を生成する。
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GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
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Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
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Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.
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Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.
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Deploy applications and websites to Vercel. Use this skill when the user requests deployment actions such as "Deploy my app", "Deploy this to production", "Create a preview deployment", "Deploy and give me the link", or "Push this live". No authentication required - returns preview URL and claimable deployment link.
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Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces and buckets.
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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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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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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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Manage Docker containers, images, volumes, networks, and Compose stacks — lifecycle ops, debugging, cleanup, and Dockerfile optimization.
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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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Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
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Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges
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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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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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Space/aerospace mission monitoring: dark command center, amber telemetry on navy, monospace precision. Functional clarity above all. For ops dashboards, build/deploy status, and real-time monitoring.
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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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