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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds real behavioral context beyond that: the price unit (cents per minute), the availability semantics when a model is supplied, and the underlying REST mapping (GET /hardware). It does not cover pagination or result size, keeping it at a 4.

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?

Three short sentences, each earning its place: what is listed, what the optional param does, and the API endpoint mapping. The scoping constraint is front-loaded and there is no filler.

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?

With no output schema and a single optional parameter, the description compensates well by naming the fields returned and the availability behavior. Minor gaps remain around ordering or throttling, but nothing essential for correct invocation is missing.

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 100%, and the schema already states the model parameter filters to compatible hardware with availability. The description restates the same behavior, adding no syntax or format detail beyond the schema, so baseline 3 applies.

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 ('List hardware configurations for dedicated endpoints') and enumerates the returned fields (GPU type/count/memory, price in cents per minute). This is clearly separable from siblings like list_models or list_endpoints without opening any schema.

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?

Explicitly says to pass a model to narrow results to compatible configurations with live availability, giving the agent a clear conditional usage rule. It stops short of naming an alternative tool or stating when not to use it, so it is strong but not exhaustive.

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