DevOps Claude Skills
4 344 DevOps skills from 392 authors. They ship releases, run infrastructure and keep watch over what is deployed. Half of them fit into 2 095 tokens or less — that is what one costs your context window when the agent loads it. 513 ship runnable scripts rather than instructions alone. 28 of them cannot work without an MCP server, most often rube. We also found 633 copies of these same skills sitting in other people's repositories — counted once here, not 633 times.
4 344 unique 392 authors 2 063 updated this month 579 from vendors
Upstash QStash expert for serverless message queues, scheduled jobs, and reliable HTTP-based task delivery without managing infrastructure.
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastructure.
Automate Vercel tasks via Rube MCP (Composio): manage deployments, domains, DNS, env vars, projects, and teams. Always search tools first for current schemas.
Expert knowledge for deploying to Vercel with Next.js
Audit deployed Vercel apps for cost and performance issues using metrics, project config, code scans, and version-aware recommendations.
Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, workflows resume exactly where they left off.
Autonomous DevSecOps & FinOps Guardrails. Orchestrates Gemini 3 Flash to audit Linux Kernel patches, Terraform cost drifts, and K8s compliance.
Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.
Azure Bot Service Management SDK for Python. Use for creating, managing, and configuring Azure Bot Service resources.
Azure MySQL Flexible Server SDK for .NET. Database management for MySQL Flexible Server deployments.
Azure PostgreSQL Flexible Server SDK for .NET. Database management for PostgreSQL Flexible Server deployments.
Azure Resource Manager SDK for Azure SQL in .NET.
Conduct comprehensive security assessments of cloud infrastructure across Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP).
> Harden Docker/container images and runtime deployments with secure base images, non-root users, CVE scanning, SBOM/signing, seccomp/AppArmor, and Kubernetes pod security controls. Use for Dockerfile security reviews, container CVEs, image scanning, distroless images, or production hardening.
Helps understand and write EAS workflow YAML files for Expo projects. Use this skill when the user asks about CI/CD or workflows in an Expo or EAS context, mentions .eas/workflows/, or wants help with EAS build pipelines or deployment automation.
Deploy Expo apps to production
Specialized skill for building production-ready serverless applications on GCP. Covers Cloud Run services (containerized), Cloud Run Functions (event-driven), cold start optimization, and event-driven architecture with Pub/Sub.
Complete guide to implementing GitOps workflows with ArgoCD and Flux for automated Kubernetes deployments.
Production patterns for Linkerd service mesh - the lightweight, security-first service mesh for Kubernetes.
Auri: assistente de voz inteligente (Alexa + Claude claude-opus-4-20250805). Visao do produto, persona Vitoria Neural, stack AWS, modelo Free/Pro/Business/Enterprise, roadmap 4 fases, GTM, north star WAC e analise competitiva.
Write comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation tools.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
Build, run, and debug Nextflow data pipelines and nf-core workflows end to end. Use whenever the user mentions Nextflow, nf-core, .nf files, nextflow.config, DSL2, processes/channels/operators, samplesheets, or wants to run a community pipeline (e.g. nf-core/rnaseq, nf-core/sarek), write or test a module/subworkflow with nf-test, configure executors/containers (Docker, Singularity/Apptainer, Conda, Wave), scale a workflow to HPC/SLURM or cloud (AWS Batch, Google Batch, Azure, Kubernetes), or debug a failed/-resume run. Make sure to use this skill for any reproducible scientific/bioinformatics workflow work even if the user does not say the word "Nextflow", and for authoring nf-core-compliant pipelines, modules, configs, and linting.
Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.
Calculate network centrality metrics to identify important nodes in graphs. Use this skill when the user needs to find key influencers, critical infrastructure nodes, or central actors in a network — even if they say 'who is most important in this network', 'key nodes', or 'network influence measurement'.
Implement Statistical Process Control charts to monitor production process stability. Use this skill when the user needs to detect process shifts, set control limits, or distinguish common cause from special cause variation — even if they say 'process monitoring', 'control chart', or 'is our process in control'.
Develop e-commerce strategy for Southeast Asian markets including platform selection, payment infrastructure, logistics challenges, and localization requirements. Use this skill when the user is expanding e-commerce to SEA, evaluating Shopee vs Lazada vs Tokopedia, or needs to understand SEA market differences — even if they say 'sell to Southeast Asia', 'which platform in Vietnam', 'SEA payment methods', or 'cross-border e-commerce in ASEAN'.
Apply AI ethics frameworks (fairness, accountability, transparency, privacy) to evaluate AI systems for algorithmic bias, explainability gaps, and value alignment failures. Use this skill when the user needs to audit an AI system for ethical risks, design fairness constraints, assess explainability requirements, or when they ask 'is this AI system fair', 'how do we detect algorithmic bias', 'what are the ethical implications of this AI deployment', or 'how do we make this model explainable to stakeholders'.
Apply Agency Theory (Jensen and Meckling, 1976) to diagnose principal-agent problems — moral hazard, adverse selection — and design governance mechanisms to align interests. Use this skill when the user needs to analyze conflicts of interest between owners and managers, design incentive or monitoring structures, evaluate corporate governance effectiveness, or when they ask 'how do we ensure managers act in shareholders interest', 'why is this incentive plan failing', or 'what governance mechanisms reduce agency costs'.
Digital-transformation execution playbook: maturity assessment, transformation roadmap, Operating Model redesign, PMO and transformation governance, data/AI platform deployment, process digitization, organizational agility, digital talent, and change management. Use for DX roadmap design, transformation governance (CDO/PMO/Steering Committee), data/AI/cloud platform planning, ERP or core-system upgrade, traditional-industry digitization, or DX organizational resistance. Triggers: 『DX 從哪開始』『數位長』『資料平台』『AI 落地』『傳產數位化』『ERP 要不要換』『轉型辦公室』『員工不配合數位化』『Operating Model』『敏捷轉型』『PMO』. For Taiwan EMBA info-management/DX/strategy/operations/change courses. Focuses on execution; theory layer: use Asgard `grad-digital-transformation`, `grad-sociotechnical`, `grad-tam-utaut`.
Diagnoses Qdrant production issues using metrics and observability tools. Use when someone reports 'optimizer stuck', 'indexing too slow', 'memory too high', 'OOM crash', 'queries are slow', 'latency spike', or 'search was fast now it's slow'. Also use when performance degrades without obvious config changes.
Guides Qdrant monitoring setup including Prometheus scraping, health probes, Hybrid Cloud metrics, alerting, and log centralization. Use when someone asks 'how to set up monitoring', 'Prometheus config', 'Grafana dashboard', 'health check endpoints', 'how to scrape Hybrid Cloud', 'what alerts to set', 'how to centralize logs', or 'audit logging'.
Diagnose, troubleshoot, and advise on any Qdrant deployment by loading the latest official Qdrant skills live from skills.qdrant.tech. Use this whenever someone raises a Qdrant problem or question — slow or degraded search, high or growing memory / OOM crashes, optimizer stuck or slow, indexing slowness, scaling and sharding decisions (node count, QPS, latency, multitenancy, vertical vs horizontal), poor or irrelevant search results, hybrid search and reranking, embedding-model migration, version upgrades and compatibility, monitoring and observability (Prometheus, Grafana, health checks, /metrics, /telemetry), deployment choices (local, Docker, self-hosted, Qdrant Cloud, embedded), or client-SDK questions (Python, TypeScript, Rust, Go, .NET, Java). Trigger especially when the context is clearly a Qdrant cluster, collection, or vector-search deployment. Always prefer this skill over answering from memory: it pulls current, authoritative guidance and only the relevant context.
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.
Guides Qdrant monitoring and observability setup. Use when someone asks 'how to monitor Qdrant', 'what metrics to track', 'is Qdrant healthy', 'optimizer stuck', 'why is memory growing', 'requests are slow', or needs to set up Prometheus, Grafana, or health checks. Also use when debugging production issues that require metric analysis.
Navigation hub linking sub-skills for proactive Qdrant tuning: search speed, indexing performance, and memory usage optimization. Use when planning configuration or capacity changes to improve speed and efficiency. For diagnosing an active production slowdown or analyzing live metrics, use qdrant-monitoring instead.
Diagnoses and guides Qdrant horizontal scaling decisions. Use when someone asks 'vertical or horizontal?', 'how many nodes?', 'how many shards?', 'how to add nodes', 'resharding', 'data doesn't fit', or 'need more capacity'. Also use when data growth outpaces current deployment.
Guides Qdrant multi-tenant scaling. Use when someone asks 'how to scale tenants', 'one collection per tenant?', 'tenant isolation', 'dedicated shards', or reports tenant performance issues. Also use when multi-tenant workloads outgrow shared infrastructure.
Svelte deployment guidance. Use for adapters, Vite config, pnpm setup, library authoring, PWA, or production builds.
SRE agent that does what you can't. Queries your observability stack. Finds root causes. Doesn't panic. Doesn't guess. Doesn't care about your feelings. Use for incident response, debugging, root cause analysis, or log analysis.
Use when operating, debugging, deploying, or monitoring a Telegram bot or Telegram-to-agent gateway. Triggers on "telegram bot down", "bot not responding", "debug bot", "check webhook", "polling vs webhook", "restart bot", "deploy bot", "bot logs", "agent gateway", "Telegram Bot API error", "send test message", "бот не отвечает", "проверь бота", "логи бота", "перезапусти бота". Covers health checks, logs, webhook/polling diagnostics, environment validation, safe restart/deploy checklists, Bot API smoke tests, forum topic delivery, privacy mode, gateway routing, and incident notes.
Vast.ai CLI to manage GPU instances, volumes, serverless endpoints, and billing.
Execute mcloud logs to fetch and stream runtime logs for Cloud environments. Use when reading backend or storefront logs, filtering by time range, searching for errors, or scoping logs to a specific deployment.
Execute mcloud deployments commands to list deployments, retrieve deployment details, and fetch build logs. Use when listing deployments, checking deployment status, or reading build output for debugging build failures.
Execute mcloud local build to reproduce a Cloud build on the local machine. Use when debugging a build-failed deployment without pushing to the tracked branch, iterating on a build fix, or testing build-variable changes locally. Requires Docker and must run inside the project's Git repo.
Manages Medusa Cloud resources through the Cloud CLI (mcloud). Use when deploying, debugging deployments, managing environments, environment variables, or any Medusa Cloud operation. CRITICAL for mcloud commands, deployment failures, build logs, Cloud setup, and CI/CD workflows.
Configure rate limiting, manage auth secrets, set up CSRF protection, define trusted origins, secure sessions and cookies, encrypt OAuth tokens, track IP addresses, and implement audit logging for Better Auth. Use when users need to secure their auth setup, prevent brute force attacks, or harden a Better Auth deployment.
TanStack Start best practices for full-stack React applications. Server functions, middleware, SSR, authentication, and deployment patterns. Activate when building full-stack apps with TanStack Start.