get_gpu_metrics

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

No annotations are provided, so the description carries the full burden. It only states it returns a snapshot and gives the endpoint; it does not disclose return format, filter effects, authentication needs, rate limits, or read-only behavior. This is a significant gap for a data query tool.

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-loaded: the first sentence states the purpose, the endpoint is included parenthetically, and examples are useful without being verbose. Every element earns its place.

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 value details are covered, but the description fails to explain the datacenter parameter or how this tool relates to alternatives like get_gpu_trends. The lack of annotation context makes this incomplete for an agent deciding how to invoke it.

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%, but the examples add meaning by showing gpu_name accepts a list of strings (e.g., 'RTX 4090', 'A100') and verified accepts a boolean. However, the datacenter parameter is completely undocumented in both the schema and the description, leaving a gap.

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 first sentence clearly states it provides a 'current snapshot of supply, demand, and pricing across GPU types,' which is a specific action on a specific resource. This also distinguishes it from sibling tools like get_gpu_trends, which implies time-series data.

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?

Examples show invocation patterns, but there is no explicit guidance on when to use this tool versus alternatives such as search_offers or get_gpu_trends. Usage context is only implied by the 'current snapshot' wording.

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