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get_partition_queues

Fetches the full queue hierarchy for a partition, including max, guaranteed, and pending resources for each queue. Raw integer values require conversion to human-readable units.

Instructions

Fetches the full queue hierarchy for a specific partition. Includes maxResource, guaranteedResource, and pendingResource for each queue. IMPORTANT: resource values are raw integers (bytes for memory, millicores for CPU). Convert these to human-readable formats (e.g., GiB or Cores) before presenting to the user.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "partitionName": "<partitionName>"
    },
    "name": "get_partition_queues"
  }
}

Input Schema

Name	Required	Description	Default
`partitionName`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 1, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Since no annotations are provided, the description carries the full burden. It adds key behavioral insight by stating that resource values are raw integers (bytes for memory, millicores for CPU) and that they must be converted to human-readable formats before presentation. It also discloses exactly which resource fields are included.

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

Conciseness5/5

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

The description is concise and front-loaded: two sentences pack the purpose, included fields, and an important conversion caveat with no redundancy or filler.

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?

Given the tool's simplicity (one required parameter) and the presence of an output schema, the description sufficiently covers what the tool does, key return fields, and a critical usage caveat. Minor aspects like exact hierarchy format are left unspecified, but overall it is complete enough for a reliable agent to 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?

The schema provides no descriptions (0% coverage), so the description must compensate. It identifies that the partitionName parameter refers to 'a specific partition,' but it does not elaborate on the parameter's format, possible values, or how to derive them. The contribution is minimal but non-zero.

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: 'Fetches the full queue hierarchy for a specific partition.' This specifies the resource (queue hierarchy) and the scope (partition), distinguishing it from sibling tools like get_partitions or get_applications_by_state.

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

Usage Guidelines4/5

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

The description effectively conveys when to use this tool: when needing queue hierarchy and resource details for a specific partition. It does not explicitly mention alternatives or exclusions, but the context is strong enough to guide selection.

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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