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mmpyro

vcluster-mcp

by mmpyro

delete_namespace_annotation

Remove a specified annotation from a Kubernetes namespace. If the annotation does not exist, the operation still succeeds.

Instructions

Delete an annotation from a namespace.

This function removes an annotation from a Kubernetes namespace. If the annotation doesn't exist, the operation is considered successful.

Args: namespace: The name of the namespace to remove the annotation from. key: The annotation key to delete. kubeconfig_path: Optional path to a kubeconfig file. If not provided, the default kubeconfig from the environment will be used.

Returns: Union[bool, str]: True on success (or if annotation didn't exist), or error object if failed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes
namespaceYes
kubeconfig_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Without annotations, the description covers key behavior: it states that deleting a non-existent annotation is considered successful, and it explains the return value (Union[bool, str]). It also clarifies the optional kubeconfig_path behavior. However, it does not disclose permission requirements or the effect of deleting a non-existent namespace.

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

Conciseness4/5

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

The description is well-structured with a summary, details, Args, and Returns sections. The first two sentences are somewhat redundant ('Delete an annotation from a namespace' vs 'This function removes an annotation from a Kubernetes namespace'), which slightly reduces conciseness.

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 description covers the purpose, all parameters, and the return behavior, making it sufficient for a simple deletion operation. It lacks explicit usage guidance and potential failure scenarios (e.g., non-existent namespace), but the output schema likely covers return details.

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

Parameters5/5

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

The schema has 0% description coverage, but the description compensates by explaining every parameter: namespace, key, and kubeconfig_path, including the default behavior when kubeconfig_path is not provided. This adds meaning beyond the schema's bare titles.

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 opens with a specific verb and resource: 'Delete an annotation from a namespace.' It clearly states the operation and the target, distinguishing it from sibling tools like get_namespace_annotations and set_namespace_annotation based on the delete action.

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

Usage Guidelines2/5

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

The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention exclusions or conditions. It simply states what the function does, leaving the agent to infer usage from the purpose alone.

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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