Lhb Board

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

With no annotations, the description carries the full burden and does so well beyond a restatement: it discloses the auto-rollback rule (max 10 days, skip weekends), the classification contract (seat type only, ignore buy/sell wording), the data limitation (no specific brokerage branches, never fabricate), and the no-recommendation policy. It also cites the concrete data source and its last-verified date. The only missing piece is any error-handling or rate-limit behavior.

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-loaded: identity and skill mapping come first, then the date rule, then output and contracts. Every clause (rollback, contract, data source) adds usable information rather than filler, though the multi-clause contract paragraph is heavy and could be tightened.

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?

Because an output schema exists the description needn't enumerate return values, yet it still summarizes the output shape and, more importantly, supplies the governance contracts (no fabrication, no recommendations) that structured fields do not carry. With annotations absent, the behavioral and output-contract coverage makes it nearly complete, lacking only failure-mode detail.

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 0%, so the description must supply parameter meaning, and it does: trade_date's empty-value behavior is fully explained (rollback to nearest trading day), and top_n's role is conveyed via the '净买入/净卖出 TopN' output framing. top_n is still only implied rather than explicitly tied to the parameter, keeping it out of the top band.

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 uses a specific verb+resource: it retrieves 龙虎榜明细 (the daily LHB detail list) and identifies its scope via the corresponding skill (laogu-lhb 龙虎榜夜报). The resource is unmistakable and clearly distinct from the sibling set (quote, fund_flow, ann_list, etc.), but it never names a sibling or states what it is *not*, so it stops short of explicit differentiation.

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?

Usage context is implied through the skill correspondence and the trade_date rollback rule, but there is no explicit 'use this when…' or routing against alternatives like fund_flow or market_snapshot. The trade_date default behavior is well specified, which helps invocation, but selection guidance is left to inference.

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