get_dragon_tiger_stats

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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds valuable behavioral context by explaining what each statistical type computes (e.g., stock_stats = listing frequency and net buy stats) and the conditional parameter dependency. This goes beyond the schema by clarifying output semantics, although it does not mention return structure or pagination.

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 two tightly packed sentences in Chinese, front-loaded with the main purpose followed by type details and a critical note. Every phrase contributes, and there is no redundancy or fluff.

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?

Given the tool's moderate complexity with conditional parameter dependencies, the description covers the essential distinctions and requirements. No output schema exists, so the description could have mentioned return format details, but it still provides enough context for an agent to invoke the tool correctly. It feels nearly complete but leaves some ambiguity about the output structure.

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 baseline is 3. The description enriches parameter understanding by providing more specific meanings for type values (e.g., stock_stats = 个股上榜频次和净买入统计 vs schema's simpler 个股上榜统计) and clarifies the period/date distinction. This adds value beyond the schema 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 Dragon-Tiger List statistical data and specifies three distinct types (stock_stats, institution, branch_rank) with concrete meanings. This differentiates it from sibling tools like get_dragon_tiger_list which likely return raw lists rather than aggregated statistics.

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 provides clear within-tool usage guidance on which type to use and explicitly notes the parameter requirements: institution requires startDate/endDate, while other types use period. However, it does not explicitly mention alternatives or when not to use this tool versus sibling tools, so it falls short of a 5.

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