Skip to main content
Glama

gpu_list_resources

Lists GPU resources and per-GPU memory for a provider or account, including eligibility flags to help choose quota-aware jobs.

Instructions

Accelerators. Memory is per GPU. Mock data are TEST FIXTURES, not a live account.

account lists that account only. There is no automatic rotation. When quota publishes eligible_gpus, each row includes eligible.

Input Schema

NameRequiredDescriptionDefault
accountNo
providerNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.6/5.0
Behavior3/5

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

With no annotations, the description does carry real behavioral context: the mock-data-as-test-fixtures caveat, per-account scoping, no automatic rotation, and the eligible field appearing when quota publishes eligible_gpus. That is genuinely useful, but it omits whether this is a pure read, auth requirements, and any pagination or error behavior.

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

Conciseness3/5

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

It is short, but the lead word 'Accelerators.' is a weak, near-contentless front-load, and the remaining text is choppy sentence fragments with odd inline code formatting. Nothing is padded, but the ordering does not surface the most decision-relevant information first.

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?

An output schema exists so return values need not be explained, but for a 2-parameter tool with zero annotation coverage the description leaves the `provider` parameter, the read-only nature, and the account-vs-provider relationship unspecified. Key gaps remain 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 both parameters. It addresses `account` (scope limited to that account) but says nothing about what `provider` filters or accepts, leaving half the parameters undocumented anywhere.

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

Purpose3/5

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

The description opens with the bare noun 'Accelerators.' and never supplies an explicit verb like 'list' or 'enumerate available GPU/accelerator resources'. It hints at content ('Memory is per GPU') but does not differentiate itself from gpu_list_providers, gpu_list_accounts, or the parallel l2kc_list_resources sibling.

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?

It states a scoping rule ('``account`` lists that account only. There is no automatic rotation.'), but gives no guidance on when to choose this tool over gpu_list_accounts/providers or the l2kc variant. No exclusions, no prerequisites, no mention of how account vs provider interact.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.