Google GKE

delete_k8s_resource

Destructive

Deletes a Kubernetes resource from a cluster. This is similar to running kubectl delete.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	Yes	Required. The name of the resource to delete.
`dryRun`	No	Optional. If true, run in dry-run mode.
`parent`	Yes	Required. The cluster, which owns this collection of resources. Format: projects/{project}/locations/{location}/clusters/{cluster}
`cascade`	No	Optional. The cascading deletion policy to use. If not specified, 'background' is used. Valid values are 'background', 'foreground', and 'orphan'.
`namespace`	No	Optional. The namespace of the resource. If not specified, "default" is used.
`resourceType`	Yes	Required. The type of resource to delete. Kubernetes resource/kind name in singular form, lower case. e.g. "pod", "deployment", "service".

Output Schema

TableJSON Schema

Name	Required	Description	Default
`errors`	No	Errors encountered during deletion.
`result`	No	Result of the delete operation.

TDQS

B3.4/5.0

Behavior3/5

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

Annotations already declare destructiveHint=true, so the description doesn't need to restate that. However, it adds no further behavioral context beyond the basic deletion, such as irreversibility, permissions, or side effects. It aligns with annotations and offers no contradictions.

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 short sentences, front-loaded with the main action and a useful analogy. Every word earns its place, and there is no redundancy or filler.

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?

Given the presence of a rich schema and annotations, the description is sufficient for a straightforward delete operation. It omits nuances like dry-run or cascade behavior, but those are captured in the schema. The description is not overly verbose and covers the core purpose.

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?

The input schema covers all 6 parameters with descriptions, including required fields and defaults. Since schema coverage is 100%, the description need not add parameter details, and it doesn't—staying neutral. This meets the baseline for high coverage.

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 clearly states the action ('Deletes a Kubernetes resource from a cluster') and provides a familiar analogy ('similar to running kubectl delete'). It distinguishes from siblings by naming the delete operation, though it does not explicitly compare with alternative operations.

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?

The description offers no explicit guidance on when to use this tool versus alternatives like patch_k8s_resource or apply_k8s_manifest. The kubectl delete analogy implies usage context, but no criteria or scenarios are given.

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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