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gpu_list_providers

Lists available GPU compute providers for Kaggle and Colab jobs, helping you compare options before submitting work. Returns mock fixture data unless real mode is enabled.

Instructions

List providers. Mock data are TEST FIXTURES, not a live account.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does surface one genuinely non-obvious trait: the returned data are test fixtures rather than a live account, so an agent shouldn't present them as real infrastructure. It says nothing about auth requirements, whether the call is a pure read, or result ordering/pagination.

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?

Two short sentences with the core action first and the important mock-data warning second; nothing is padded. It is terse to the point of thinness, but no sentence is wasted.

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?

An output schema exists, so return-value explanation isn't required, and the mock-data warning covers the biggest trap. Still, for a zero-param entry point into a provider/account/resource hierarchy, the description never explains what a provider is or how it relates to the account and resource listing tools.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The schema is empty and fully described, and the description correctly implies no input is needed.

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?

"List providers" names a verb and resource, but it is essentially the tool name with the gpu_ prefix stripped and says nothing about scope or what a provider is. It also gives no basis for choosing it over the sibling l2kc_list_providers, which appears to do the same thing for the other backend.

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 statement of when to call this versus l2kc_list_providers, gpu_list_accounts, or gpu_list_resources, all of which sit adjacent in the toolset. The mock-data note is a caveat about data provenance, not guidance on selecting the tool.

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