get_category_sales

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

No annotations are provided, so the description carries the burden. It discloses an important implementation detail: '需交叉 Categories API + Products + Orders' (requires cross-referencing multiple APIs), which signals potential complexity. However, it does not mention performance, side effects, or return format beyond listing the metrics, leaving room for more transparency.

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 a single, information-dense sentence that front-loads the main function, lists key output fields, and notes the data dependency. Every part adds value with no redundancy, making it concise and well-structured.

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?

The description covers the essential output metrics (revenue, volume, product count) and the cross-API dependency, which is sufficient for an agent to select and invoke the tool. It does not mention the channel filter or explicitly differentiate from channel comparison, but the schema covers those details, and with no output schema, the listed metrics provide adequate context.

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?

The input schema has 100% coverage with detailed descriptions for start_date, end_date, and channel, including performance warnings. The tool description itself adds no parameter-specific guidance, so it does not go beyond the schema; the baseline of 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?

The description clearly states the tool aggregates sales data '依商品分類' (by product category) and specifies the exact output metrics: revenue, sales volume, and product count. This distinguishes it from sibling tools like get_sales_summary or get_channel_comparison, which focus on different breakdowns.

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 implies usage for category-level sales reporting but does not explicitly state when to use this tool over alternatives among the many report siblings. No exclusions or comparisons are provided, so the usage context is only implied by the purpose.

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