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Glama

Google GKE

by com.googleapis.container

get_cluster

Read-onlyIdempotent

Gets the details of a specific GKE cluster.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesRequired. The name (project, location, cluster) of the cluster to retrieve. Specified in the format `projects/*/locations/*/clusters/*`.
readMaskNoOptional. The field mask to specify the fields to be returned in the response. Use a single "*" to get all fields. Default: autopilot,createTime,currentMasterVersion,currentNodeCount,currentNodeVersion,description,endpoint,fleet,location,name,network,nodePools.locations,nodePools.name,nodePools.status,nodePools.version,releaseChannel,resourceLabels,selfLink,status,statusMessage,subnetwork.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorsNoErrors encountered during cluster retrieval.
clusterNoA string representing the Cluster object in JSON format.

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and idempotentHint, and the description aligns with a safe read operation. However, the description adds no extra behavioral context beyond the annotations, such as field masking defaults or pagination behavior, so it meets the baseline without enriching transparency.

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 a single focused sentence with no redundant content. Every word contributes to the purpose, achieving maximum conciseness.

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 get operation with a comprehensive input schema, an output schema, and strong annotations, the description is adequate. It lacks explicit differentiation from get_k8s_cluster_info, but the 'GKE cluster' specificity mitigates ambiguity, so it is nearly complete.

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%, so the schema fully documents both parameters. The tool description does not add any additional meaning beyond the schema, 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.

Purpose5/5

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

The description uses a specific verb ('Gets') and clearly identifies the resource ('details of a specific GKE cluster'). This distinguishes it from sibling tools like list_clusters or get_node_pool, as it targets a single GKE cluster's details.

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 provided about when to use this tool versus alternatives such as list_clusters or get_k8s_cluster_info. The description gives no exclusions or explicit context for selection, leaving the agent to infer usage.

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.

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