solver_list_model_deployments

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

With no annotations, the description carries the burden of behavioral disclosure. It correctly implies a read-only GET operation, but it does not mention pagination, output format, or authorization requirements. The 'certification-backed' qualifier adds useful domain context.

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 tight sentences front-load the core action and endpoint, then provide a cross-tool next step. Every word contributes, with no repetition or 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?

For a simple parameterless list operation, the description supplies the resource, endpoint, and a downstream action. The absence of an output schema is not critical given the straightforward nature of a list call, though a brief note on returned fields would make it fully complete.

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?

The tool has zero parameters and the empty input schema is fully self-explanatory. The description adds no parameter details, but none are needed; the baseline of 4 for zero-parameter tools 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?

The description uses the specific verb 'List' with a well-defined resource: the tenant's certification-backed model deployments, and names the API endpoint. It is clearly distinct from sibling tools like solver_list_arms and solver_list_sources.

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 second sentence provides actionable context: after listing deployments, the agent can enable one as an arm via solver_enable_model_arm. This makes the tool's role in a workflow clear, although it does not explicitly enumerate alternatives or when not to use it.

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