measure

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

With no annotations provided, the description carries the full burden. It discloses the tool's purpose and the kernel's tolerance for degenerate input, adding valuable behavioral context beyond the schema. It does not cover error cases or side effects, but for a measurement tool this is sufficient.

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 concise and well-structured: it fronts the purpose, then provides a motivational usage note, and ends with parameter documentation. No unnecessary words; every sentence earns its place.

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 tool with two simple string parameters and an existing output schema, the description is complete. It covers what the tool does, why it is useful, and all parameters. Return value details are delegated to the output schema, so no redundancy.

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 description includes a dedicated Args section with clear one-line definitions for both doc_name and obj_name. Since schema description coverage is 0%, this fully compensates and explains the meaning and role of each parameter.

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 clearly states the tool measures an object's real geometry with a specific list of metrics (volume, area, bounding box, isValid, face/edge/vertex counts, and cylindrical-vs-planar counts). This specificity distinguishes it from siblings like measure_gap, which measure distance/gaps.

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 gives explicit guidance to use this tool to verify the results of mutating operations, with a strong rationale about FreeCAD's kernel tolerating degenerate input. This provides clear context, though it does not explicitly name alternatives such as measure_gap for exclusion.

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