4 308 DevOps skills from 392 authors. They ship releases, run infrastructure and keep watch over what is deployed. Half of them fit into 2 096 tokens or less — that is what one costs your context window when the agent loads it. 507 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.
4 308 unique 392 authors 2 038 updated this month 543 from vendors
| Optimize ClickUp API usage costs through plan selection, request reduction, caching, and usage monitoring. "clickup pricing", "clickup plan comparison", "clickup API usage".
| Deploy ClickUp API integrations to Vercel, Fly.io, and Cloud Run with secure secrets management and health checks. "clickup Cloud Run", "clickup Fly.io", "clickup hosting".
| Monitor ClickUp API integrations with metrics, tracing, structured logging, and alerting using Prometheus, OpenTelemetry, and Grafana. "monitor clickup", "clickup alerts", "clickup tracing", "clickup dashboard".
| Production readiness checklist for ClickUp API v2 integrations covering auth, rate limits, error handling, monitoring, and rollback. "clickup prod ready", "deploy clickup to production".
| Handle ClickUp API rate limits with backoff, queuing, and header monitoring. Use when hitting 429 errors, implementing retry logic, or optimizing API throughput against ClickUp's per-plan rate limits. "clickup retry", "clickup backoff", "clickup request queue".
| This skill enables Claude to analyze and optimize cloud costs. It identifies areas for potential savings, generates cost reports, and suggests configuration changes to reduce expenses. Use this skill when the user asks to "optimize cloud costs", "reduce cloud spending", "generate a cost report", or similar requests related to cloud resource expenses. It is especially useful when the user provides details about their cloud environment (e.g., AWS, Azure, GCP). The skill leverages best practices for cost optimization and provides production-ready configurations.
| Cloud Function Generator - Auto-activating skill for GCP Skills. Part of the GCP Skills skill category.
| Cloud Logging Sink Setup - Auto-activating skill for GCP Skills. Part of the GCP Skills skill category.
| Cloud Monitoring Alert - Auto-activating skill for GCP Skills. Part of the GCP Skills skill category.
| Cloud Run Service Config - Auto-activating skill for GCP Skills. Part of the GCP Skills skill category.
| Cloud Scheduler Job Creator - Auto-activating skill for GCP Skills. Part of the GCP Skills skill category.
| Cloud Sql Instance Setup - Auto-activating skill for GCP Skills. Part of the GCP Skills skill category.
| Cloud Tasks Queue Setup - Auto-activating skill for GCP Skills. Part of the GCP Skills skill category.
| Cloudformation Template Creator - Auto-activating skill for AWS Skills. Part of the AWS Skills skill category.
| Cloudfront Distribution Setup - Auto-activating skill for AWS Skills. Part of the AWS Skills skill category.
| Cloudwatch Alarm Creator - Auto-activating skill for AWS Skills. Part of the AWS Skills skill category.
| Optimize CodeRabbit costs through seat management, repo selection, and review scope tuning. Use when analyzing CodeRabbit billing, reducing per-seat costs, or implementing usage monitoring and budget optimization. Trigger with phrases like "coderabbit cost", "coderabbit billing", "reduce coderabbit costs", "coderabbit pricing", "coderabbit expensive", "coderabbit budget".
| Use when deploying CodeRabbit org-wide, creating shared configurations, or onboarding development teams to AI code review. Trigger with phrases like "deploy coderabbit", "coderabbit org rollout", "coderabbit multi-repo", "coderabbit onboarding", "coderabbit team setup".
| Monitor CodeRabbit review effectiveness with metrics, dashboards, and alerts. Use when tracking review coverage, measuring comment acceptance rates, or building dashboards for CodeRabbit adoption across your organization. Trigger with phrases like "coderabbit monitoring", "coderabbit metrics", "coderabbit observability", "monitor coderabbit", "coderabbit alerts", "coderabbit dashboard".
| Configure CI/CD for Cohere integrations with GitHub Actions and automated testing. Use when setting up automated testing for Chat/Embed/Rerank, configuring CI pipelines, or testing Cohere-powered applications. Trigger with phrases like "cohere CI", "cohere GitHub Actions", "cohere automated tests", "CI cohere", "cohere pipeline".
| Optimize Cohere costs through model selection, token budgets, and usage monitoring. Use when analyzing Cohere billing, reducing API costs, or implementing usage monitoring and budget alerts. Trigger with phrases like "cohere cost", "cohere billing", "reduce cohere costs", "cohere pricing", "cohere expensive", "cohere budget".
| Deploy Cohere-powered applications to Vercel, Fly.io, and Cloud Run. Use when deploying Cohere API v2 apps to production, configuring platform-specific secrets, or setting up deployment pipelines. Trigger with phrases like "deploy cohere", "cohere Vercel", "cohere production deploy", "cohere Cloud Run", "cohere Fly.io".
| Configure Cohere across development, staging, and production environments. Use when setting up multi-environment deployments, configuring per-environment API keys, model selection, and rate limit strategies. Trigger with phrases like "cohere environments", "cohere staging", "cohere dev prod", "cohere environment setup", "cohere config by env".
| Set up comprehensive observability for Cohere API v2 with metrics, traces, and alerts. Use when implementing monitoring for Chat/Embed/Rerank operations, setting up dashboards, or configuring alerts for Cohere integrations. Trigger with phrases like "cohere monitoring", "cohere metrics", "cohere observability", "monitor cohere", "cohere alerts", "cohere tracing".
| Execute Cohere production deployment checklist and rollback procedures. Use when deploying Cohere integrations to production, preparing for launch, or implementing go-live procedures for Cohere-powered apps. Trigger with phrases like "cohere production", "deploy cohere", "cohere go-live", "cohere launch checklist".
Collect comprehensive infrastructure performance metrics across compute, storage, network, containers, load balancers, and databases. Use when monitoring system performance or troubleshooting infrastructure issues. Trigger with phrases like "collect infrastructure metrics", "monitor server performance", or "track system resources".
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| Integrate CoreWeave deployments into CI/CD pipelines with GitHub Actions. Use when automating container builds, deploying inference services from CI, or validating GPU manifests in pull requests. Trigger with phrases like "coreweave CI", "coreweave github actions", "coreweave pipeline", "automate coreweave deploy".
| Deploy KServe InferenceService on CoreWeave with autoscaling and GPU scheduling. Use when serving ML models with KServe, configuring scale-to-zero, or deploying production inference endpoints on CoreWeave. Trigger with phrases like "coreweave inference service", "coreweave kserve", "coreweave model serving", "deploy model on coreweave".
| Deploy inference services on CoreWeave with Helm charts and Kustomize. Use when deploying multi-model inference, managing GPU deployments at scale, or templating CoreWeave manifests. Trigger with phrases like "deploy coreweave", "coreweave helm", "coreweave kustomize", "coreweave deployment patterns".
| Deploy a GPU workload on CoreWeave with kubectl. Use when running your first GPU job, testing inference, or verifying CoreWeave cluster access. Trigger with phrases like "coreweave hello world", "coreweave first deploy", "coreweave gpu test", "run on coreweave".
| Configure CoreWeave Kubernetes Service (CKS) access with kubeconfig and API tokens. Use when setting up kubectl access to CoreWeave, configuring CKS clusters, or authenticating with CoreWeave cloud services. Trigger with phrases like "install coreweave", "setup coreweave", "coreweave kubeconfig", "coreweave auth", "connect to coreweave".
| Set up local development workflow for CoreWeave GPU deployments. Use when building containers locally, testing YAML manifests, or iterating on model serving configurations before deploying. Trigger with phrases like "coreweave dev setup", "coreweave local testing", "develop for coreweave", "coreweave container build".
| Migrate ML workloads from AWS/GCP/Azure to CoreWeave GPU cloud. Use when moving inference services from hyperscaler GPU instances, migrating training pipelines, or evaluating CoreWeave vs cloud GPU costs. Trigger with phrases like "migrate to coreweave", "coreweave migration", "move from aws to coreweave", "coreweave vs aws gpu".
| Configure CoreWeave across development, staging, and production environments. Use when setting up multi-environment GPU infrastructure, separating namespaces, or managing per-environment GPU quotas. Trigger with phrases like "coreweave environments", "coreweave staging", "coreweave multi-env", "coreweave namespace setup".
| Set up GPU monitoring and observability for CoreWeave workloads. Use when implementing GPU metrics dashboards, configuring alerts, or tracking inference latency and throughput. Trigger with phrases like "coreweave monitoring", "coreweave observability", "coreweave gpu metrics", "coreweave grafana".
| Reference architecture for CoreWeave GPU cloud deployments. Use when designing ML infrastructure, planning multi-model serving, or establishing CoreWeave deployment standards. Trigger with phrases like "coreweave architecture", "coreweave design", "coreweave infrastructure", "coreweave best practices".
| Secure CoreWeave deployments with RBAC, network policies, and secrets management. Use when hardening GPU workloads, managing model access, or configuring namespace isolation. Trigger with phrases like "coreweave security", "coreweave rbac", "secure coreweave", "coreweave secrets".
| Upgrade CoreWeave deployments and migrate between GPU types. Use when migrating from A100 to H100, upgrading CUDA versions, or updating inference server versions. Trigger with phrases like "upgrade coreweave", "coreweave gpu migration", "coreweave cuda upgrade", "migrate coreweave".
| Monitor CoreWeave cluster events and GPU workload status. Use when tracking pod lifecycle events, monitoring GPU utilization, or alerting on inference service health changes. Trigger with phrases like "coreweave events", "coreweave monitoring", "coreweave pod alerts", "coreweave gpu monitoring".
| Cost Optimization Analyzer - Auto-activating skill for AWS Skills. Part of the AWS Skills skill category.
| This skill enables Claude to monitor and analyze CPU usage patterns within applications. It helps identify CPU hotspots, analyze algorithmic complexity, and detect blocking operations. Use this skill when the user asks to "monitor CPU usage", "optimize CPU performance", "analyze CPU load", or "find CPU bottlenecks". It assists in identifying inefficient loops, regex performance issues, and provides optimization recommendations. This skill is designed for improving application performance by addressing CPU-intensive operations.
| Execute this skill enables AI assistant to create intelligent alerting rules for proactive performance monitoring. it is triggered when the user requests to "create alerts", "define monitoring rules", or "set up alerting". the skill helps define thresholds, rou... Use when generating or creating new content. Trigger with phrases like 'generate', 'create', or 'scaffold'.
| Deploy applications to Kubernetes with production-ready manifests. Supports Deployments, Services, Ingress, HPA, ConfigMaps, Secrets, StatefulSets, and NetworkPolicies. Includes health checks, resource limits, auto-scaling, and TLS termination. Use when working with creating kubernetes deployments. Trigger with 'creating', 'kubernetes', 'deployments'.
| Configure BYOK API keys for OpenAI, Anthropic, Google, Azure, and custom models in Cursor. Triggers on "cursor api key", "cursor openai key", "cursor anthropic key", "own api key cursor", "BYOK cursor", "cursor azure key".
| Configure Customer.io CI/CD integration with automated testing. Use when setting up GitHub Actions, integration test suites, or pre-commit validation for Customer.io code. "customer.io pipeline", "customer.io automated testing".
| Deploy Customer.io integrations to production cloud platforms. Use when deploying to Cloud Run, Vercel, AWS Lambda, or Kubernetes with proper secrets management and health checks. "customer.io kubernetes", "customer.io lambda", "customer.io vercel".
| Configure Customer.io multi-environment setup with workspace isolation. Use when setting up dev/staging/prod workspaces, environment-aware clients, or Kubernetes config overlays. "customer.io dev prod", "customer.io workspace isolation".