Lists available Kaggle and Colab accounts with quota status so agents can choose a provider, excluding credentials; mock fixtures are used unless real mode is enabled.
List accounts. Mock data are TEST FIXTURES, not a live account.
Credential values are not included. Quota exhaustion does not rotate to another account of the same provider.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden and does disclose important traits: the data are mock TEST FIXTURES rather than live accounts, credential values are omitted, and quota exhaustion does not rotate to another account. It still omits explicit read-only/auth/rate-limit details, but adds substantial context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description front-loads 'List accounts' and follows with three short caveats; there is no boilerplate or repetition. The quota-rotation sentence is somewhat tangential, and line breaks are awkward, but the text remains compact and useful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool with an output schema, the description needs mainly to clarify purpose and behavioral caveats, which it does. It is slightly incomplete because it does not explain the gpu_ versus l2kc_ provider distinction or when this account list should be preferred over its sibling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters and schema description coverage is 100%, so there are no parameter semantics to document. The rubric baseline for a zero-parameter tool is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource with 'List accounts.' It is clear enough to distinguish this from job/quota/resource tools, but it does not differentiate this GPU account listing from the sibling l2kc_list_accounts or explain what account scope is being listed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit when-to-use guidance, prerequisites, or alternatives. It does not explain when an agent should call gpu_list_accounts instead of gpu_list_providers or l2kc_list_accounts, so the user must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.