get_mass_properties

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

With no annotations provided, the description fully discloses behavior: it is read-only, returns data in specific units, lists all return fields with types and units, and notes the dependency on a material being set. No surprises or contradictions.

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 thorough but not overly verbose. It is well-structured with sections for purpose, return dict, caveats, uses, and example. The front-loading of the core purpose is good. Could be slightly more concise, but the structure aids readability.

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 no output schema, the description provides a complete explanation of the tool's functionality and return values. It also provides context for typical use cases and prerequisites, making it fully self-contained for an agent.

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 are no parameters, so the schema coverage is 100%. The description adds value by detailing the output format and units, which goes beyond the empty input schema. Baseline 4 is appropriate as the description compensates for the lack of parameters.

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?

Clearly states the tool reads mass properties (mass, volume, surface area, etc.) for the active part or assembly. The verb 'read' and specific resource 'mass properties' make the purpose unambiguous. It distinguishes itself from sibling tools by specifying its exact output fields.

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?

Explicitly mentions common use cases (quoting, lightening pass, inertia analysis) and provides a concrete example. Includes caveats: requires material to be set, behavior with default material, and references set_material as a prerequisite. This provides clear when-to-use and actionable guidance.

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