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raffelprama

MCP cldkctl Server

by raffelprama

cldkctl_create_daemonset

Create a DaemonSet in Kubernetes using Cloudeka's cldkctl CLI. Specify DaemonSet configuration data to deploy pods across cluster nodes.

Instructions

Call the cldkctl_create_daemonset endpoint

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daemonset_dataYesDaemonSet data
Behavior1/5

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

No annotations are provided, so the description must fully disclose behavior. It fails to indicate that this is a destructive write operation (creating a DaemonSet), lacks details on permissions, side effects (e.g., pod scheduling), or response format. This omission is critical for a tool with mutation capabilities.

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

Conciseness2/5

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

The single sentence 'Call the cldkctl_create_daemonset endpoint' is overly concise to the point of under-specification. It wastes no words but fails to convey necessary information, making it ineffective rather than efficiently structured.

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

Completeness1/5

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

For a tool that creates a Kubernetes DaemonSet (a complex, stateful resource), the description is completely inadequate. With no annotations, no output schema, and minimal guidance, it doesn't address creation behavior, error handling, or integration with sibling tools, leaving significant gaps for an AI agent.

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 100%, with the parameter 'daemonset_data' documented as 'DaemonSet data'. The description adds no additional meaning beyond this, such as required fields or examples. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema handles the heavy lifting.

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

Purpose2/5

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

The description 'Call the cldkctl_create_daemonset endpoint' is tautological—it restates the tool name without explaining what it does. It lacks a specific verb-resource combination (e.g., 'Create a Kubernetes DaemonSet') and doesn't differentiate from siblings like 'cldkctl_create_deployment' or 'cldkctl_create_statefulset', leaving the purpose vague.

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

Usage Guidelines1/5

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. The description doesn't mention prerequisites (e.g., Kubernetes context), exclusions, or related tools (e.g., 'cldkctl_edit_daemonset' for updates), making it misleadingly simplistic for a creation operation.

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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