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gpu_get_quota

Reads GPU quota snapshots for a specified Kaggle or Colab account, optionally refreshing the cached entry first, so you can check available capacity before submitting jobs.

Instructions

Quota snapshots. Mock data are TEST FIXTURES, not a live account.

account reads that account only. There is no automatic rotation. refresh drops the per-account quota cache entry before reading.

Input Schema

NameRequiredDescriptionDefault
accountNo
refreshNo
providerNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and usefully discloses that mock data are test fixtures, that account scoping has no automatic rotation, and that refresh clears the per-account cache before reading. It still omits provider behavior and any auth/error/rate-limit context.

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 four short lines, front-loaded with the snapshot purpose and fixture warning, then parameter notes. It is compact and structured with backticks, though the opening phrase is terse.

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

Completeness3/5

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

Given no annotations, 0% schema coverage, and three optional parameters, the description leaves provider semantics and sibling routing unexplained. An output schema exists, so return values need not be described, but the remaining gaps are clear.

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 compensate; it explains ``account`` as a scoped read and ``refresh`` as a cache drop. It says nothing about ``provider`` and does not clarify what a null account means, leaving one of three parameters completely undocumented.

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 calls the tool "Quota snapshots" but never states a clear retrieval verb or scope such as "returns GPU quota for an account/provider." It is identifiable as quota-related, but not clearly differentiated from siblings like l2kc_get_quota or gpu_refresh_quota.

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 explains that ``account`` reads only that account and that ``refresh`` drops the cache, but gives no when-to-use guidance, exclusions, or routing to sibling tools such as gpu_refresh_quota. The agent must infer the invocation context.

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