k8s_scale_kubernetes_node_pool

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It notes smart identifier resolution and a minimum target count, but it does not reveal that scaling is a mutating operation with potential side effects like deleting nodes when scaling down, whether the operation is asynchronous, or what permissions are required.

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

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

The description is compact and well-structured with clear Args and Returns sections. Every sentence adds useful information, and there is no filler or redundant restating of the tool name.

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

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

The description covers all required parameters and states the return type at a high level, which is adequate for a straightforward scaling operation. However, it lacks behavioral caveats such as scaling-down effects, asynchronous behavior, permissions, or how to obtain the identifiers it mentions. The absent annotations make this gap more significant.

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

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

With 0% schema description coverage, the description fully compensates by explaining each parameter: cluster_identifier accepts a label or ID, nodepool_identifier accepts a label or ID, and target_node_count is a target number with a minimum of 1. This adds meaning well beyond the raw schema types.

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

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

The description opens with a specific verb and resource: "Scale a node pool to the target number of nodes." This clearly distinguishes the tool from sibling operations like creating, updating, deleting, or listing node pools. The mention of smart identifier resolution adds useful scope without blurring the core purpose.

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

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

The action is clear enough that an agent can infer this tool is for horizontal scaling, but the description does not explicitly state when to prefer it over alternatives such as k8s_update_kubernetes_node_pool. It also provides no exclusions or preconditions, so the usage context is only implied.

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