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

No annotations are provided, so the description must carry the full disclosure burden. It usefully adds the per-call cost ($0.05 USDC) and lists the output fields (platform, 30-day low/high/average, gap), but it does not explicitly state that the operation is read-only or mention rate limits.

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 front-loaded with the core purpose, followed by a concrete example that illustrates both input and output. It is efficiently sized with no extraneous content.

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 simple one-parameter query with no output schema, the description covers the return fields and billing model, which is sufficient. A modest gap remains: it does not direct users to list_gpu_models for valid GPU names, which could prevent input errors.

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?

Schema description coverage is 0%, so the description must compensate for the single 'gpu' parameter. The example 'gpu=\'RTX 4090\'' gives a format hint, but it does not specify case sensitivity, accepted model name lists, or validation rules.

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: querying the current lowest price of a given GPU across all platforms, and it lists the returned metrics. It distinguishes itself from a historical tool by emphasizing '现在的' (current), but it does not explicitly contrast with siblings like gpu_history or list_gpu_models.

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 example demonstrates one usage, but there is no explicit guidance on when to use this tool versus gpu_history or other siblings. No exclusions or alternative conditions are stated.

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