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

No annotations are provided, so the description carries the burden and does most of it: it discloses that the data is post-close, that `date` may fall back with `is_fallback=true` and `requested_date` vs `date` divergence, and that `net_buy` is a signed net figure that can be negative. It also flags the access requirement ('机构版专属'). It stops short of stating read-only/rate-limit characteristics, but the disclosure level is well above adequate for a data-read tool.

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?

Purpose and the sibling split are front-loaded and bolded; the warning block is high-value. The long enumeration of row fields is largely redundant with the output schema that already exists, which costs some tightness.

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 three-parameter, no-required-param read tool with an output schema, everything an agent needs is present: what the rows represent, sign conventions, row count expectation (~51/day), date fallback semantics, and routing guidance. No meaningful gap remains.

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; the description still adds meaning on `date` by explaining the fallback contract (`requested_date` / `date` / `is_fallback`) beyond the schema's 'blank = latest trading day'. It does not elaborate on `sort` enumerations or `limit` ceiling, which remain schema-only.

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?

States a specific resource and scope: all market-wide stocks with institutional seat participation on the dragon-tiger list for a given trading day, returned in one call. It explicitly contrasts itself with the sibling `ashare_lhb_seats` (single-stock brokerage drill-down vs. market-wide screening), so an agent can pick the right tool without opening either schema.

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?

Gives concrete trigger phrasings ('今天机构买了哪些票 / 机构在龙虎榜买了什么 / 哪些票有机构参与') and an explicit routing rule against the sibling: '今天机构买什么' → this tool, '这只票是谁买的' → ashare_lhb_seats. Both when-to-use and when-to-use-the-alternative are covered.

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