list_gpu_models
列出所有可查询的 GPU 卡型(免费)。付费查询前先调这个拿准确名称。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
列出所有可查询的 GPU 卡型(免费)。付费查询前先调这个拿准确名称。
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden: it discloses the operation is free and that it precedes paid queries, which tells the agent about cost and sequencing. It stops short of explicitly saying it is read-only or what shape the result takes, but for a zero-param lookup the risk surface is small.
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?
Two sentences with no filler. The core action comes first, followed by the conditional workflow hint, so it reads front-loaded.
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?
An output schema exists, so return values need no explanation, and with zero parameters the description covers everything needed to invoke the tool. It could add one clause on what to do with the returned names, but the essentials are present.
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 takes no parameters, so there is nothing to disambiguate; baseline 4 applies. Schema description coverage is 100% and the empty property set is consistent with the 'list all' framing.
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?
States a specific verb and resource: listing all queryable GPU card models, and flags that it costs nothing. It does not explicitly name the sibling it differs from (gpu_price, gpu_history), but 'free' vs 'paid query' implicitly separates it from the paid lookups.
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?
Gives a clear workflow rule: call this before a paid query to obtain exact card names. This covers the when-to-use case well, though it doesn't state when-not-to-use or name the specific paid sibling tools it should precede.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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