Scale a Kubernetes Deployment to a specified number of replicas, adjusting pod count to match workload demands.
Scale a Deployment.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| replicas | Yes | ||
| namespace | No | ||
| session_name | No | default |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Scale a Deployment' without mentioning side effects, prerequisites (e.g., deployment must exist), idempotency, or permissions. This is minimal and does not inform the agent about what happens when scaling fails or whether it is reversible.
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, short sentence, which is appropriately concise. However, it is under-specified; it does not front-load any usage context or parameter hints. While it is not verbose, its brevity borders on under-specification, so a score of 3 reflects its efficiency without substance.
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?
Given the tool has four parameters and an output schema, the description is extremely thin. It does not explain what the output represents, any preconditions, or how the scaling operation interacts with the cluster. The description is incomplete for an agent to call the tool correctly without additional schema inspection.
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?
Schema description coverage is 0%, meaning the description adds no information about the parameters. It does not mention that 'name' and 'replicas' are required, nor explain the role of 'namespace' or 'session_name'. With four parameters and zero coverage, the description must compensate but does not, making the tool's parameters opaque.
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 states a specific verb ('Scale') and resource ('a Deployment'), making the tool's purpose clear. However, it does not differentiate from sibling tools like k8s_restart or k8s_apply, so it lacks explicit sibling distinction.
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 k8s_apply or k8s_restart. The description simply states the action without context or exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.