model_info

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

There are no annotations, so the description must carry the behavioral disclosure burden. 'Return' implies a read-only operation with no side effects, and 'current model' indicates state dependence, which is useful. However, it does not explicitly say whether it modifies state, requires the model to be loaded first, or what happens if no model exists.

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 a single, front-loaded sentence with no filler. Every word contributes meaning, and it is appropriately sized for a zero-parameter introspection tool.

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?

Given zero parameters and an output schema, the description is largely sufficient for an agent to call this tool. The main missing context is an explicit statement that this is a safe, read-only introspection call and whether a model must already be loaded.

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 accepts zero parameters, so parameter semantics are trivially clear. Per the baseline for zero-parameter tools, the description need not explain inputs. The schema already confirms there are no arguments.

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 a specific verb ('Return') and identifies the resource ('structure of the current model'), clearly distinguishing it from the many model-manipulation siblings like add_sphere, run_solver, or save_model. However, it does not clarify what kind of structure is returned (e.g., geometry hierarchy, API schema, or mesh topology), leaving some room for interpretation.

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 is given about when to use this tool versus alternatives such as evaluate, solver_status, or load_model. The name implies an introspection utility, but the description does not state a recommended use case or mention that it can be used to inspect the current model before performing operations.

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