e2e_tir_list_gpu_skus

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 usefully discloses return content (pricing and specs) and 'List' implies a read-only operation, but it says nothing about permissions, pagination, or how filtering affects results.

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?

A single tight sentence that front-loads the action and resource and spends its remaining words on concrete examples. Nothing is wasted.

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 optional-parameter list tool with no output schema, the description is adequate but thin: it explains the return content yet leaves the semantics of the service/location/project filters and result shape to inference.

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% with three well-documented optional parameters (service, location, project_id), so the schema already does the heavy lifting. The description adds no parameter-level meaning beyond that, matching the baseline of 3.

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 (List) and resource (NVIDIA GPU hardware SKUs on E2E TIR) and even enumerates concrete examples (H100, A100, L40S...), so an agent immediately knows what domain it covers. No sibling tool overlaps with GPU SKU enumeration, so it is easy to distinguish.

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 description never states when to call this tool versus alternatives, nor does it mention prerequisites or exclusions. Usage (e.g. before provisioning a notebook or training cluster) must be inferred entirely by the agent.

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