get_model_info

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

No annotations exist; description does not disclose any behavioral traits beyond the action. It does not mention that the tool is read-only, requires an open model, or any potential side effects or error conditions.

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?

Single sentence that efficiently states the purpose and output details. No redundant or extra content.

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, parameter-less info tool, the description sufficiently explains what is returned. Minor gaps: no mention of prerequisites (e.g., model must be open) or error handling, but not critical for typical use.

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?

Tool has zero parameters; schema coverage is 100%. Description adds value by specifying the exact information returned, which is not inferable from the schema alone. Baseline of 4 is appropriate.

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?

Description clearly states the tool retrieves general model information and explicitly lists the data fields (name, file path, unit system, entity/layer/material counts). This distinguishes it from sibling tools that focus on specific components (e.g., list_layers, list_entities).

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?

Description implies use for overall model stats but does not explicitly guide when to use this vs. sibling tools like list_layers or list_entities. No when-not-to-use or alternative recommendations are provided.

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