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get_k8s_rollout_status

Read-onlyIdempotent

Checks the current rollout status of a Kubernetes resource. This is similar to running kubectl rollout status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesRequired. The name of the resource to check.
parentYesRequired. The cluster to check rollout status in. Format: projects/{project}/locations/{location}/clusters/{cluster}
namespaceNoOptional. The namespace of the resource. If not specified, "default" is used for namespace-scoped resources.
resourceTypeYesRequired. The type of resource to check. e.g. "deployment", "daemonset", "statefulset".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorsNoErrors encountered during rollout status check.
resultNoThe result of the rollout status check.

TDQS

A3.8/5.0
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, which the description's 'Checks' aligns with. The description adds the notion of 'current' status, which implies a point-in-time check rather than a blocking wait, but it does not elaborate on whether the call waits for rollout completion or returns immediately, leaving potential ambiguity given the kubectl analogy.

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 long, front-loads the core purpose in the first sentence, and uses the second sentence for a helpful analogy. Every word earns its place, with no redundant content.

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?

The tool is a simple read-only operation with complete schema coverage, clear annotations, and an output schema. The description sufficiently orients the agent, and the kubectl analogy adds relevant context. No significant gaps exist for a tool of this complexity.

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 has 100% coverage with detailed descriptions for all four parameters, so the schema carries the full semantic burden. The description provides no additional parameter-level details, which is acceptable given the schema's completeness; baseline 3 applies.

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: 'Checks the current rollout status of a Kubernetes resource.' It includes a specific verb ('checks') and resource ('rollout status'), and the kubectl analogy ('similar to running `kubectl rollout status`') precisely conveys the intended operation, distinguishing it from generic get/describe tools.

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 kubectl analogy gives implicit guidance on when to use the tool (when you would run `kubectl rollout status`), but it does not explicitly mention alternatives or exclusion criteria among sibling tools. No when-not-to-use guidance is provided.

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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