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clusterrole_delete

Remove a ClusterRole from a Kubernetes cluster to manage access control permissions. Specify the cluster context and role name to delete it.

Instructions

Delete a ClusterRole from the cluster.

Args: context_name: The Kubernetes context name name: The ClusterRole name

Returns: Status of the deletion operation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
context_nameYes
nameYes

Implementation Reference

  • The main handler function decorated with @mcp.tool() for executing the clusterrole_delete tool. It deletes the specified ClusterRole using the Kubernetes RBAC API.
    @mcp.tool()
    @use_current_context
    @check_readonly_permission
    def clusterrole_delete(context_name: str, name: str):
        """
        Delete a ClusterRole from the cluster.
    
        Args:
            context_name: The Kubernetes context name
            name: The ClusterRole name
    
        Returns:
            Status of the deletion operation
        """
        rbac_v1: RbacAuthorizationV1Api = get_api_clients(context_name)["rbac"]
        rbac_v1.delete_cluster_role(name=name)
        return {"name": name, "status": "Deleted"}
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states it's a deletion operation but lacks details on permissions required, whether deletion is reversible, side effects, or error handling. This is a significant gap for a destructive tool with zero annotation coverage.

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 front-loaded with the main purpose, followed by structured parameter and return sections. It is efficient with no wasted sentences, though the parameter explanations are very brief.

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

Completeness2/5

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

For a destructive tool with no annotations, no output schema, and low schema coverage, the description is incomplete. It misses critical behavioral details like safety warnings, return value specifics, or error conditions, making it inadequate for informed use.

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?

Schema description coverage is 0%, but the description adds minimal semantics by listing parameters with brief explanations ('context_name: The Kubernetes context name', 'name: The ClusterRole name'). However, it does not fully compensate for the coverage gap, as it lacks details on parameter formats or constraints.

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 action ('Delete') and resource ('ClusterRole from the cluster'), making the purpose specific and unambiguous. It distinguishes from siblings like clusterrole_create, clusterrole_get, and clusterrole_list by focusing on deletion.

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?

No explicit guidance on when to use this tool versus alternatives is provided. The description does not mention prerequisites, risks, or comparisons to other deletion tools (e.g., role_delete), leaving usage context unclear.

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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