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

With no annotations provided, the description appropriately discloses that lower-tier subscriptions result in HTTP 403, and it describes the return format. It does not cover rate limits or other edge behaviors, but for a read-only market data endpoint this is reasonable.

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 compact and well-organized: a title line, a package requirement, an Args block, and a Returns block. Every sentence contributes useful information with no filler.

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 four-parameter data retrieval tool with no annotations and an output schema, the description provides all necessary context: data source, access restrictions, parameter formats, and return fields. It is fully self-contained.

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 description's parameter section largely repeats schema info, but it adds the important constraint that trade_date is mutually exclusive with start_date/end_date. It also lists output fields, adding context beyond the input schema.

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 identifies the tool as providing Dragon-Tiger List (institutional seats) market data, which is a specific resource and distinguishes it from the sibling top_list (general top list). It lacks an explicit verb but the intent is unambiguous.

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 explicitly states the PRO package requirement and the mutual exclusion between trade_date and start_date/end_date, providing actionable usage constraints. It does not explicitly contrast with alternatives like top_list, but the institutional-seat qualifier implies a distinct use case.

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