measure

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains that measurements are independent of build resolution, describes the output semantics (distances on w-/w+ and h-/h+ axes, section area), and clarifies the difference between bone-chain and world-axis modes. It does not mention side effects or permissions, but this appears to be a read-only measurement tool, and the description's detail about what is computed and how is substantial.

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 dense but well-organized, with the two modes clearly separated by 'along =' clauses. It front-loads the core purpose and then details each mode. It is somewhat long, but every sentence adds necessary information about output semantics or usage. The structure is logical and scannable.

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 measurement tool with no output schema and no annotations, the description is quite complete: it explains what is measured, how the output is structured, and how to select modes. It does not explicitly document the 'name' parameter or provide examples of return values, but the description's detail about section areas and axis ranges gives an agent enough to invoke it correctly. The lack of an output schema is partially compensated by the description's explanation of what the tool returns.

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?

Schema description coverage is 0%, so the description must compensate for the schema's lack of parameter documentation. It does this well: it explains 'along' can be a bone name/list or 'x'/'y'/'z', describes 'samples' as evenly spaced t, and mentions 'lo' and 'hi' as optional bounds. The 'name' parameter is not explicitly described, but it is clearly the model name from context. The description adds significant meaning beyond the bare schema types.

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 cross-section sizes as numbers, and distinguishes two modes: along a bone chain or along a world axis. It names the resource (the model) and the specific operation (measure), and the examples ('y' gives body width and height, 'z' shows where legs merge) make the purpose concrete. It is clearly differentiated from siblings like 'look' or 'check' by focusing on quantitative cross-section measurements.

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 explains when to use the tool ('Use it to find pinches, bulges and lumps along a limb') and gives concrete examples of axis modes. It does not explicitly state when not to use it or name alternative tools, but the context is clear enough for an agent to select it for measurement tasks. The two modes are well explained with conditions (bone chain vs world axis, optional lo/hi range).

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