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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: data source ('GACC's English site final monthly report'), units ('US$1,000'), and the conditional output structure with and without hs_section. No contradiction with annotations exists.

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 information-rich, front-loading the core data scope and metric before explaining the filter behavior. The Chinese translation is redundant for many agents but not harmful, and the overall length is appropriate for the complexity of the tool.

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 carries the burden of explaining return structure, and it does so reasonably: it states the section-level default, the chapter-level expansion with hs_section, the metric dimensions (month, YTD, YoY), and the unit of value. It could specify the exact output fields, but the provided information is sufficient for an agent to understand and invoke the tool correctly.

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 baseline is 3, but the description adds value beyond the schema by explaining the behavioral consequence of each hs_section state: without it, all sections plus TOTAL; with it, the matching section's individual chapters. It also reinforces the accepted input forms (2-digit code or free text) with concrete examples.

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 identifies the resource ('China's merchandise exports/imports'), the organizing dimension (HS Section and 2-digit HS chapter), and the metric mix (monthly, year-to-date, year-on-year percent change). It clearly distinguishes this commodity-focused tool from siblings like china_trade_by_country by emphasizing the HS classification basis and the specific default output of 21 sections plus TOTAL.

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 clear behavioral usage context: omitting hs_section returns all sections, while supplying a chapter code or free text returns that section's chapters. It does not explicitly say when to prefer this tool over china_trade_by_country or china_trade_summary, but the usage conditions for optional parameters are explicit and actionable.

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