Google GKE

get_k8s_cluster_info

Read-onlyIdempotent

Gets cluster endpoint information. This is similar to running kubectl cluster-info.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`parent`	Yes	Required. The parent cluster. Format: projects/{project}/locations/{location}/clusters/{cluster}

Output Schema

TableJSON Schema

Name	Required	Description	Default
`errors`	No	Errors encountered during cluster info retrieval.
`clusterInfo`	No	The cluster info of the resource. Displays address and port information about the Kubernetes control plane and other services running within the cluster such as CoreDNS and Metrics-server. Example: "The Kubernetes control plane is at 10.128.0.10:6443. CoreDNS is running at https://192.0.2.1:6443/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy Metrics-server is running at 127.0.0.1:8080"

TDQS

B3.4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds the `kubectl cluster-info` analogy, which gives some context about the output behavior, but this is limited beyond what annotations and the word 'Gets' already convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loads the action, and contains no fluff. Every word contributes to understanding what the tool does.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter tool with an output schema and rich annotations, the description is mostly sufficient. However, it lacks differentiation from the sibling `get_cluster`, which could leave the agent unsure which tool to invoke in a given context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single `parent` parameter, including its format. The description does not add any additional parameter information, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Gets' with a clear resource 'cluster endpoint information', and the analogy to `kubectl cluster-info` clarifies the scope. However, it does not explicitly distinguish from the sibling tool `get_cluster`, which might have overlapping functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives like `get_cluster` or `list_clusters`. The `kubectl cluster-info` analogy implies a use case, but it does not provide boundaries or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.6/5.0

Disambiguation4/5

Most tools target distinct actions and resources, but a few pairs could confuse agents, such as get_cluster (GKE cluster details) vs get_k8s_cluster_info (kubectl cluster-info), or apply_k8s_manifest vs patch_k8s_resource. Overall, descriptions help clarify the differences.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in lowercase snake_case (e.g., create_cluster, list_node_pools, get_k8s_logs). There are no mixed conventions or unpredictable naming variations.

Tool Count4/5

With 23 tools, the server covers both GKE cluster management and in-cluster Kubernetes operations, which justifies the count. It is slightly on the heavier side but remains within a reasonable scope for such a broad domain.

Completeness3/5

The tool surface covers create, read, update, and list operations for clusters and node pools, but notably lacks delete_cluster and delete_node_pool. This leaves an obvious lifecycle gap that agents cannot work around without additional tooling.

Resources

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