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

Annotations already declare a safe read-only, non-open-world operation, so the bar is lower. The description adds genuine value beyond that: source coverage and years, the kake_cost_ratio definition, and the caveat that figures are industry averages rather than a firm's actual purchase cost.

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?

Purpose, formula, optional BEA behavior and the industry-average caveat are front-loaded before the examples. It is dense bilingual text but each clause carries information; only the duplicated EN/JA phrasing adds mild bulk.

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?

An output schema exists, so return format need not be described. The description supplies source coverage, the derived metric definition, the optional BEA branch, and the key scope caveat, which is sufficient for an 8-param all-optional tool.

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 parameter and the baseline is 3. The description goes further by showing the semantic link between commodity/include_bea and the optional BEA 2007 margin structure, and by mapping naics prefixes to trade categories.

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?

States a specific verb+resource: returns U.S. wholesale and retail gross margins by NAICS, with named data sources (Census AWTS/ARTS/AIES) and the derived kake_cost_ratio. The resource is distinctive, but it does not distinguish itself from the sibling get_us_price_chain, which is also about a producer-to-purchaser price/margin chain.

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?

Examples (naics='4233', '444110') and the scope caveat 'industry averages, not any firm's cost' imply usage without stating when to pick this over alternatives. There is no explicit when-not guidance or named sibling such as get_us_price_chain for a full chain request.

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