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Found 30 Skills
Kubernetes cluster operations: kubectl commands, manifest generation, Helm charts, RBAC, debugging, and deployment strategies.
Safety guardrails for destructive commands. Warns before rm -rf, DROP TABLE, force-push, git reset --hard, kubectl delete, and similar destructive operations. User can override each warning. Use when touching prod, debugging live systems, or working in a shared environment. Use when asked to "be careful", "safety mode", "prod mode", or "careful mode".
This skill should be used when users need to interact with Kubernetes clusters via kubectl CLI. It covers pod management, deployment operations, log viewing, debugging, resource monitoring, scaling, ConfigMaps, Secrets, Services, and all standard kubectl operations. Supports multiple clusters (production, staging, local k3s) with predefined aliases. Triggers on requests mentioning Kubernetes, k8s, pods, deployments, containers, or cluster operations.
Use when assessing or reviewing Kubernetes workloads running on Amazon EKS for best practice compliance, including pod configuration, security posture, observability, networking, storage, image security, and CI/CD practices. Requires kubectl and awscli access to the target cluster. Triggers on "assess my EKS workloads", "check k8s best practices", "assess container workloads", "evaluate pod security", "workload compliance check", "EKS workload assessment", "检查 K8s 工作负载", "评估容器最佳实践", "审计 EKS 应用", "检查 Pod 配置", "容器安全评估", "工作负载合规检查".
Manage Tencent Cloud TKE (Tencent Kubernetes Engine) clusters and workloads. Use when the user asks to: list clusters, check cluster / node health, list pods or services, scale a Deployment, do a rolling restart, fetch kubeconfig, view recent K8s events, manage node pools. Combines the official tencentcloud-sdk-python TKE client (cluster metadata) with kubectl for in-cluster operations.
Kubernetes operations including deployment, management, troubleshooting, kubectl mastery, and cluster stability. Covers K8s workloads, networking, storage, and debugging pods. Use when user mentions Kubernetes, K8s, kubectl, pods, deployments, services, ingress, ConfigMaps, Secrets, or cluster operations.
Kubernetes operations playbook for deploying services: core objects, probes, resource sizing, safe rollouts, and fast kubectl debugging
Assist with Kubernetes interactions including debugging (kubectl logs, describe, exec, port-forward), resource management (deployments, services, configmaps, secrets), and cluster operations (scaling, rollouts, node management). Use when working with kubectl, pods, deployments, services, or troubleshooting Kubernetes issues.
Debug Kubernetes pods, nodes, and workloads using kubectl debug. Covers ephemeral containers, pod copying, node debugging, debug profiles, and interactive troubleshooting sessions. Use when user mentions kubectl debug, debugging pods, ephemeral containers, node debugging, or interactive troubleshooting in Kubernetes clusters.
Kubernetes deployment, management, and troubleshooting. Activate for k8s, kubectl, pods, deployments, services, ingress, namespaces, and container orchestration tasks.
Diagnoses and fixes Kubernetes issues with interactive remediation. Use when pods crash (CrashLoopBackOff, OOMKilled), services unreachable (502/503, empty endpoints), deployments stuck (ImagePullBackOff, pending). Also use when tempted to run kubectl fix commands directly without presenting options, or when user says "just fix it" for K8s issues.
Systematic Kubernetes troubleshooting and incident response. Use this skill whenever the user mentions Kubernetes, K8s, kubectl, pods, containers, or clusters. Triggers include diagnosing CrashLoopBackOff, ImagePullBackOff, OOMKilled, or Pending pods, responding to production incidents, troubleshooting node NotReady or DiskPressure, debugging service connectivity or networking, investigating PVC or storage failures, analyzing performance degradation, checking cluster health, troubleshooting Helm releases, and conducting post-incident reviews.