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OpenShift 4 MCP Server

get_machine_config_pool

Inspect a MachineConfigPool's current conditions and machine counts to verify rollout status and node availability.

Instructions

Get MachineConfigPool detail: conditions and machine counts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
clusterNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the disclosure burden. It does reveal the type of information returned ('conditions and machine counts'), which is useful behavioral context. However, it says nothing about side effects, permissions, error behavior, or whether the operation is strictly read-only (though 'get' strongly implies it). The description adds some value but leaves safety and failure behavior undisclosed.

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 a single concise sentence with no wasted words. It front-loads the primary action ('Get MachineConfigPool detail') and immediately specifies key output attributes. It is appropriately sized for the tool's simplicity, though it could pack more useful context without becoming verbose.

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 tool with two parameters, no parameter descriptions, no annotations, and no usage guidance, the description is thin. The output schema may cover the return shape, but the agent is left to guess the meaning of 'cluster' and the conditions for selecting this tool over siblings like 'list_machine_config_pools' or 'get_machine'. The missing contextual details are significant for correct invocation.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must explain the parameters, but it does not. The 'name' parameter can be inferred as the pool name from the tool name, but 'cluster' (optional, default '') is completely unexplained. The description adds no meaning beyond the schema's bare type information, failing to compensate for the missing schema descriptions.

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

Purpose4/5

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

The description uses a specific verb ('Get') and resource ('MachineConfigPool detail') and adds concrete output specifics ('conditions and machine counts'), making it clear this is a read operation for a single pool's detail. It implicitly separates itself from the sibling 'list_machine_config_pools' by emphasizing 'detail', though it does not explicitly name the sibling or contrast the two.

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?

There is no guidance on when to use this tool versus alternatives. It does not mention prerequisites, when to prefer 'get_machine_config_pool' over 'list_machine_config_pools', or any exclusions. Usage is only implied by the verb 'Get', which is weak guidance for an agent deciding among many similar resource tools.

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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