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patch_k8s_resource

Destructive

Patches a Kubernetes resource. This is similar to running kubectl patch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesRequired. The name of the resource to patch.
patchYesRequired. The patch to apply in JSON format.
parentYesRequired. The cluster to patch the resource in. Format: projects/{project}/locations/{location}/clusters/{cluster}
namespaceNoOptional. The namespace of the resource. If not specified, "default" is used.
patchTypeNoOptional. The patch strategy to apply. Valid values are "strategic", "merge", or "json". If not specified, "strategic" patch type will be used.
resourceTypeYesRequired. The type of resource to patch. e.g. "pods", "deployments", "services".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorsNoErrors encountered during patching.
resultNoThe result of the patch operation.

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already disclose destructiveHint=true, readOnlyHint=false, and idempotentHint=false, so the description does not need to repeat these. The description adds minimal behavioral context beyond the kubectl analogy; it does not explain side effects or requirements. This is adequate given the annotations, but not especially rich.

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 that are front-loaded with the core action and immediately provide a useful analogy. Every word contributes; 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 rich input schema (100% parameter coverage) and annotations (destructiveHint, readOnlyHint), the description is succinct but sufficient. The analogy to `kubectl patch` provides practical context for users familiar with Kubernetes tooling. It does not explain all nuances (e.g., patch types), but these are covered in the schema, and an output schema exists.

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 100% of parameters with descriptions, so the baseline is 3. The description itself adds no parameter-level details, but this is acceptable because the schema fully documents each parameter (e.g., patchType valid values, namespace default).

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 clearly states the tool's function: 'Patches a Kubernetes resource.' The verb 'patch' is specific and distinguishes it from sibling tools like apply_k8s_manifest, delete_k8s_resource, and get_k8s_resource. It also adds the apt comparison to `kubectl patch`, reinforcing the operation type.

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

Usage Guidelines3/5

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

The description implies usage via the analogy to `kubectl patch`, suggesting it's for partial updates to existing resources. However, it does not explicitly state when to use this tool over apply_k8s_manifest or other alternatives, nor does it provide exclusions. The guidance is implicit rather than explicit.

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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