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

Annotations already declare a safe, idempotent, closed-world read, so the description's job is to add operational context. It does: the response carries a confidence badge and a reason that must be passed on, and refused measurements should be relayed with the given reason. That is real behavioral guidance beyond the annotations.

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 output list and the usage condition are front-loaded across a compact set of sentences, each carrying information. Slightly dense in the opening enumeration, but nothing is padding.

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?

With no output schema, the description must describe the return, and it does: size variants plus a confidence badge and reason, along with how to handle refusals. It is close to complete for this tool's complexity, though it says little about ambiguous or edge-case measurement handling.

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 coverage is 100%, so underbust, bust, and unit are fully documented in the schema with instructions and an enum. The description only restates 'inches or cm, decimals allowed', which duplicates the schema rather than adding format or validation detail. Baseline 3 is correct.

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 states a specific transformation (measurements in, bra size out) and enumerates the exact outputs: base US size, sister sizes, UK, EU/French, and letter size. It implicitly separates itself from bra_size_at_brand via 'wants her size in general', but never names the sibling explicitly.

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?

'Use this when a shopper gives her measurements and wants her size in general' gives a clear triggering context, and the 'in general' phrasing contrasts with the brand-specific sibling. It also covers the refusal case, though it stops short of naming alternatives outright.

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