kubectl_scale

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

The annotation already indicates destructiveness, but the description adds no further behavioral context, such as what happens to existing pods or the impact on the cluster. For a mutation tool, more detail is expected beyond the annotation.

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 a single sentence, which is concise but lacks substance. It does not earn its place by providing unique value beyond the tool name and schema.

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?

Despite 5 parameters and no output schema, the description is too brief. It fails to explain the scaling operation's effect, what the output contains, or how to handle errors. The tool's complexity demands more context.

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?

All parameters are described in the schema, so the description does not need to add much. However, it does not explain how the 'replicas' parameter interacts with resource scaling or that 'resourceType' can target other resources besides deployments.

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 explicitly states the action (scale) and the resource (Kubernetes deployment), making the tool's purpose clear. It distinguishes from siblings like kubectl_apply or kubectl_patch through the specific verb and resource, though it could be more explicit.

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?

No guidance is provided on when to use this tool versus alternatives such as kubectl_apply for updating deployments or kubectl_rollout for managing rollouts. The description does not mention prerequisites or scenarios where scaling is appropriate.

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