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

The readOnlyHint annotation already covers the safety profile, so the bar is lower. The description adds the underlying REST mapping (GET /v2/hardware), which is useful context, but says nothing about error behavior (e.g., unknown model), what the returned configuration includes, or any constraints.

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 compact sentences with no filler, front-loading the resource and scope before the REST endpoint detail. Nothing is padded or redundant.

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 read-only single-parameter tool, this is close to sufficient, and the absence of an output schema means return values need not be explained. However, leaving the overlap with deepinfra_get_gpu_availability unresolved is a real selection risk.

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?

There is a single required parameter fully documented in the schema (100% coverage), so the schema does the heavy lifting. The description's 'for a given model' merely restates the parameter's meaning without adding format, naming, or source details.

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: retrieving the hardware options/GPU configuration for a given model. The purpose is clear on its own, but it does not differentiate itself from the sibling deepinfra_get_gpu_availability, which sounds like the same concept, so an agent cannot confidently choose between them from the text alone.

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?

No guidance on when to use this tool versus alternatives is given. The most relevant alternative, deepinfra_get_gpu_availability, is never mentioned, even though the two overlap significantly and the agent has no way to know which one answers 'what GPUs are available/free'.

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