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

Annotations already cover the safety profile (readOnly, idempotent, closed-world), so the description is free to spend itself on behaviour an agent cannot infer: it uses the same charts and the same matcher as the ALLR product page, and it explicitly refuses to guess when a chart or measurement is missing. That refusal behaviour is the single most important thing to know before calling it.

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?

A single dense paragraph that front-loads the core action and scope before moving to units, return values, and the failure mode — every sentence carries information. The unit/category mapping slightly duplicates the schema descriptions, which is the only wasted motion.

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 an output schema present the description need not enumerate return fields, yet it usefully sketches them (label, EU/US/UK equivalents, snugness, chart link). For a tool with 8 optional parameters and no required ones, it makes the mutual requirement explicit. The only gap is telling the agent how to obtain a product_id when it has none.

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 the schema already documents each measurement, its unit, and the product_id/brand+category dependency. The description restates the centimetre convention and the category-to-measurement mapping, which is useful reinforcement but adds little beyond the structured fields; baseline 3 applies.

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?

Specific verb (recommend) plus resource (a size) and precise scope (from body measurements, for a specific product or brand+category, using the manufacturer's own published chart). It is clearly distinguishable from siblings like search_gear or get_product_offers, which locate products rather than translate measurements into sizes.

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?

It states the two entry paths (product_id, or brand + category) and the fallback to known_size when no measurement is given, and it sets expectations for the failure case. What it lacks is routing guidance to siblings — e.g. telling the agent to call search_gear first when it only has a product name and no id.

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