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Found 329 Skills
Production server monitoring stack covering Prometheus, Node Exporter, Grafana, Alertmanager, Loki, and Promtail on bare-metal or VM Linux hosts. USE WHEN: - Setting up monitoring for a new production server or VPS - Configuring Prometheus scrape targets for application or system metrics - Creating Grafana dashboards and datasource provisioning - Writing Alertmanager routing rules with email/Slack notifications - Implementing the PLG stack (Promtail + Loki + Grafana) for log aggregation - Performing live system diagnostics with htop, iotop, nethogs, ss, vmstat, iostat - Setting up uptime monitoring with UptimeRobot or healthchecks.io DO NOT USE FOR: - Kubernetes-native observability (use the kubernetes skill instead) - Application-level APM (distributed tracing with Jaeger/Tempo — use observability skill) - Cloud-managed monitoring (CloudWatch, GCP Monitoring, Azure Monitor) - Windows Server monitoring
Automates declarative resource creation and provisioning for data pipelines, supporting BigQuery, Dataform, Dataproc, BigQuery Data Transfer Service (DTS), and other resources. It manages environment-specific configurations (dev, staging, prod) through a deployment.yaml file. Use when: - Modifying or creating deployment.yaml for deployment settings. - Resolving environment-specific variables (e.g., Project IDs, Regions) for deployment. - Provisioning supported infrastructure like BigQuery datasets/tables, Dataform resources, or DTS resources via deployment.yaml. Do not use when: - Resources already exist. - Managing resources not supported by `gcloud beta orchestration-pipelines resource-types list`. - Managing general cloud infrastructure (VMs, networks, Kubernetes, IAM policies), which are better suited for Terraform. - Infrastructure spans multiple cloud providers (AWS, Azure, etc.). - Already uses Terraform for the target resources.
Apply and enforce cloud resource tagging strategies across AWS, Azure, GCP, and Kubernetes for cost allocation, ownership tracking, compliance, and automation. Use when implementing cloud governance, optimizing costs, or automating infrastructure management.
Comprehensive container image security scanning and remediation. Analyzes Docker images for OS package vulnerabilities, application dependencies, and Dockerfile best practices. Use when: - User asks to scan a Docker image or container - User mentions "container security" or "image vulnerabilities" - User wants to secure a Dockerfile - User asks about base image security - Agent is working with Docker, Kubernetes, or container deployments
Sets up and configures Google Kubernetes Engine (GKE) clusters for production use. Use when creating new GKE clusters, choosing between Autopilot vs Standard modes, configuring networking (VPC-native, private clusters), setting up node pools, or planning cluster architecture for Spring Boot microservices. Includes regional vs zonal decisions, security hardening, and resource provisioning guidance.
Ultimate 25+ years expert-level backend skill covering FastAPI, Express, Node.js, Next.js with TypeScript. Includes ALL databases (PostgreSQL, MongoDB, Redis, Elasticsearch), ALL features (REST, GraphQL, WebSockets, gRPC, Message Queues), comprehensive security hardening (XSS, CSRF, SQL injection, authentication, authorization, rate limiting), complete performance optimization (caching, database tuning, load balancing), ALL deployment strategies (Docker, Kubernetes, CI/CD), advanced patterns (microservices, event-driven, saga, CQRS), ALL use cases (e-commerce, SaaS, real-time, high-traffic), complete testing (unit, integration, E2E, load, security). Route protection, middleware, authentication implementation in PERFECTION. Use for ANY backend system requiring enterprise-grade security, performance, scalability, and architectural excellence.
Expert knowledge for Azure Container Instances development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and deployment. Use when configuring ACI networking, standby pools, GitHub Actions deploys, Spot containers, or GPU workloads, and other Azure Container Instances related development tasks. Not for Azure Container Apps (use azure-container-apps), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Virtual Machines (use azure-virtual-machines), Azure App Service (use azure-app-service).
Guide for configuring the Infisical Agent — a client daemon that manages token lifecycle and renders secrets via Go templates without modifying application code. Covers the full YAML config format, all 6 auth methods (Universal Auth, Kubernetes, AWS IAM, Azure, GCP ID Token, GCP IAM), sinks, template functions (listSecrets, listSecretsByProjectSlug, getSecretByName, dynamicSecret), polling, on-change commands, and caching. Use this skill when someone asks about: Infisical Agent, agent config file, agent templates, rendering secrets to files, sidecar secret injection, token renewal, infisical agent command, or 'how do I use the Infisical Agent to inject secrets'.
Retrieve, inject, and manage secrets from Keeper Vault using KSM CLI (ksm). Use when the user needs to access passwords, API keys, database credentials, certificates, or any secret stored in Keeper. Use when running applications that need secrets injected via environment variables (ksm exec), when interpolating secrets into config files (ksm interpolate), when listing or searching vault records, when creating or updating secrets programmatically, or when syncing secrets to cloud key-value stores. Also use when the user mentions 'keeper', 'ksm', 'keeper secrets', 'keeper vault', 'keeper notation', 'keeper://', or asks about retrieving credentials for CI/CD, Docker, Kubernetes, or any DevOps pipeline. Prefer this skill over hardcoding credentials. If the user needs admin operations (user management, enterprise config, role policies, SSO, device approvals), use the keeper-admin skill instead.
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".
Build GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.
Set up comprehensive infrastructure monitoring with Prometheus, Grafana, and alerting systems for metrics, health checks, and performance tracking.