get_plate_quotation

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It states the output is formatted as a Markdown table, which is helpful, but it does not disclose if the operation is read-only, requires authentication, or has rate limits. It adequately conveys the return format but lacks completeness on traits like side effects or prerequisites.

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 relatively concise, with a clear sentence explaining the tool, followed by structured Args, Returns, and Examples sections. However, it mixes Chinese and English (first line in Chinese, rest in English), which may reduce clarity. Overall, it is efficient 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?

For a simple two-parameter tool with an output schema, the description covers the core purpose, parameter meanings, and return format. It lacks usage guidelines and fails to mention error handling or edge cases, but given the existence of an output schema and the tool's simplicity, it is adequately complete.

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 description adds significant meaning beyond the input schema, which has 0% coverage. It explains that plate_type takes values 1, 2, 3 corresponding to regional, industry (default), and concept plates, and page_size defaults to 10. Examples further clarify usage. This fully compensates for the schema's lack of descriptions.

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 retrieves top N plate market data by percentage change from East Money Network, specifying plate types like industry, concept, and regional. It is specific about the resource and verb, though it does not explicitly differentiate from siblings like 'get_plate_fund_flow' or 'get_current_plate_changes', but the context of '涨跌幅前N' (top N by change) provides implicit distinction.

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?

No explicit guidance on when to use this tool versus alternatives is provided. The description gives parameter examples but does not mention scenarios, prerequisites, or comparisons to sibling tools like get_billboard_data or get_plate_fund_flow. The agent must infer usage from context.

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