Run a local diagnostic report to check GPU tooling readiness for Kaggle and Colab jobs, verifying CLI availability without submitting real work or billed usage.
Local doctor report. Mock data are TEST FIXTURES, not a live account.
Does not execute kaggle or colab. CLI presence is shutil.which.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
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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 useful traits: mock data are test fixtures, the tool does not execute kaggle or colab, and CLI presence is checked via shutil.which. However, it does not explicitly state that the report is read-only, what side effects if any exist, or what permissions/prerequisites are needed.
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 is compact and front-loads the purpose before adding caveats. Each sentence provides relevant context, though the opening phrase remains somewhat vague.
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 diagnostic tool with an output schema, the description does not need to explain return values. However, it leaves out what the report actually diagnoses and why an agent should choose gpu_doctor over the similarly named l2kc_doctor 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?
The tool has zero parameters, so there are no parameter semantics to document. The baseline for a parameterless 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 says it produces a "Local doctor report," which gives the resource and local scope but does not clearly state what the diagnostic report checks or what "doctor" means in this context. It also does not distinguish it from the sibling l2kc_doctor tool.
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?
There is no explicit guidance on when to call gpu_doctor versus l2kc_doctor or any other sibling. The description provides caveats about mock data and non-execution, but these are behavioral details rather than usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.