Execute and manage Kubernetes clusters via kubectl commands. Query resources, deploy applications, debug containers, manage configurations, and monitor cluster health. Use when working with Kubernetes clusters, containers, deployments, or pod diagnostics.
Security Analysis
medium confidenceThe skill's instructions and scripts are coherent with a kubectl helper, but metadata omits required runtime dependencies (kubectl, kubeconfig, python3) and the package includes scripts that can access sensitive cluster data — review before granting access to any real cluster or credentials.
The name, description, SKILL.md, README, and helper scripts all align with a kubectl helper: querying resources, deploying, debugging, and node maintenance. This capability legitimately needs kubectl and access to a kubeconfig. However, the registry metadata listed no required binaries or env vars despite the skill explicitly requiring kubectl and optionally KUBECONFIG/KUBECTLDIR in documentation — an inconsistency.
The runtime instructions and scripts call kubectl for queries, logs, exec, cp, drain, rollout, etc., which is expected for a kubectl skill. These operations can read wide-ranging cluster state (including secrets via kubectl get secrets, logs, pods, configmaps) — this is normal for the tool but high sensitivity: the skill will have access to anything the kubeconfig permits. The scripts prompt for confirmation for destructive operations (node drain) and use safe dry-run suggestions, which is appropriate.
There is no install spec (instruction-only), so nothing is downloaded or written by an installer. The README/SKILL.md recommend standard package-manager installs (brew/apt/yum) for kubectl which is low risk. The package itself includes shell scripts (no external fetched code), so install risk is low — but included scripts will run locally when invoked.
Registry metadata declared no required env vars or binaries, but SKILL.md and README explicitly require kubectl (binary) and a kubeconfig (default ~/.kube/config) and mention KUBECONFIG/KUBECTLDIR; scripts also invoke python3 for json.tool. The mismatch between declared requirements and actual instructions is an incoherence that could lead to surprise (e.g., the agent or user may not realize kubeconfig access is needed). Additionally, because kubectl operations can access secrets and cluster credentials, ensure only least-privileged kubeconfig credentials are used.
The skill does not request always:true, does not modify other skills or system settings, and is user-invocable. It can be invoked autonomously per platform defaults, which increases blast radius if the agent is compromised, but that is normal and not unique to this skill.
Guidance
This package is a straightforward kubectl helper, but before installing or invoking it: 1) ensure you trust the author or inspect the scripts locally (they are plain shell scripts); 2) never point it at a kubeconfig with cluster-admin or broad privileges — use least-privileged credentials or a test cluster; 3) be aware the skill will run kubectl commands that can read secrets, logs, configmaps and exec into pods; 4) check that your environment actually has kubectl (v1.20+), python3 if you want pretty JSON output, and that KUBECONFIG is set to the intended file; 5) ask the maintainer to update the registry metadata to declare required binaries/env vars so requirements match the documentation.
Latest Release
v1.0.0
Initial release of kubectl-skill. - Execute and manage Kubernetes clusters using kubectl commands. - Query, deploy, update, debug, and monitor pods, deployments, nodes, and other resources. - Manage kubeconfig, switch contexts, and handle namespaces easily. - Includes troubleshooting, scaling, rollout, and node maintenance examples. - Supports advanced output formats, dry-run modes, and global kubectl flags. - Requires kubectl (v1.20+) and an active kubeconfig connection.
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