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frenoid

YuniKorn MCP Server

by frenoid

get_partitions

Retrieve general information and statistics for all cluster partitions, including total capacity, used capacity, and node counts, to monitor resource usage.

Instructions

Retrieves general information and statistics for all partitions in the cluster. Useful for seeing total cluster capacity, used capacity, and node counts. IMPORTANT: resource values (memory, cpu) are returned as raw integers (bytes for memory, millicores for CPU). Convert these to human-readable formats (e.g., GiB or Cores) before presenting to the user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses a key behavioral trait: resource values are returned as raw integers (bytes/millicores) and must be converted to human-readable formats. This is valuable beyond the basic read operation implied by 'Retrieves.' It does not mention permissions or side effects, but for a read-only tool the provided detail is substantial.

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 two sentences, front-loaded with the purpose and followed by the critical unit-conversion note. Every sentence earns its place with no redundant wording.

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

Completeness5/5

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

Given the tool has no parameters, an output schema exists, and sibling tools give surrounding context, the description is sufficiently complete. It covers what the tool returns, its scope, and an essential caveat about raw units, so the agent has enough information to use it correctly.

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

Parameters4/5

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

The input schema has zero parameters, which yields a baseline of 4. The description adds no parameter-specific information because none exist, but it does clarify that the tool covers 'all partitions' and the type of data retrieved, which still aids understanding.

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 states a specific verb ('Retrieves') and resource ('partitions in the cluster'), and clarifies the scope ('all partitions'). It also lists the kind of information (total cluster capacity, used capacity, node counts), which distinguishes it from sibling tools like get_partition_queues that focus on queues rather than partitions.

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 gives clear context for when to use the tool: 'Useful for seeing total cluster capacity, used capacity, and node counts.' It implies the tool is for cluster-level statistics but does not explicitly mention alternatives or when not to use it, so it just misses the top score.

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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