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

With no annotations, the description carries the full burden and delivers real behavioral facts: hotmoney currently returns no data, 龙虎榜 is published only after close (~18:00), and an empty date resolves to the most recent trading day. It does not mention permissions, caching, or rate limits, but for a public read-only data endpoint those are minor omissions.

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 dense but front-loads the type taxonomy first, then usage triggers, then caveats, so an agent can stop reading once it has what it needs. It is longer than strictly necessary (the type-by-type return enumeration and three separate ⚠️ blocks), but no sentence is pure 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 two-parameter, zero-required lookup tool with an output schema already present, the description covers everything an agent needs: what each mode returns, which mode to avoid, publication timing, default date behavior, and the sibling to use for per-stock data. Return-value explanation is correctly delegated to the output schema.

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 description coverage is 100% so the baseline is 3, and the description goes beyond it by explaining what each enum value of `type` actually returns rather than just listing the values as the schema does. The `date` parameter semantics are left to the schema, which already covers them, so it does not reach 5.

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 states the specific resource (market-level 龙虎榜 leaderboards) and enumerates all six type values with what each returns (净买/买卖额, 机构买入, 席位买入额, 胜率, etc.), so an agent knows exactly what this tool produces. It also explicitly distinguishes itself from the sibling ashare_fund, which handles per-stock 上榜明细.

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 explicit trigger phrases ("今天机构买了什么/龙虎榜/高胜率席位/活跃席位用这个"), a when-not-to-use rule (per-stock details go to ashare_fund), and a routing override for the broken type (hotmoney 暂无数据，建议改用 all/activeseat/winbuy). This is about as complete as usage guidance gets.

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