lawbotter_law_query向法老在线 AI 引擎发起法规查询：基于自建法律法规数据库（国家法律/司法解释/行政法规/部门规章）检索并生成带法条依据的回答。参数：keyword（必填，查询关键词/问题，如“劳动合同 试用期 辞退”）。返回：sessionId（会话 ID，可用于 lawbotter_followup 追问）、content（AI 回答正文）、usageStatus（匿名额度信息）。注意：回答基于数据库检索结果生成，若内容为空或不确定，应如实告知用户；匿名调用有限额（usageStatus.remaining 可查看剩余次数）。
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | Yes | 查询关键词或法律问题，如“劳动合同 试用期 辞退” |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It usefully discloses that answers are generated from database retrieval, that empty/uncertain results should be reported honestly, that anonymous calls are quota-limited, and that usageStatus.remaining shows remaining calls—behavioral context beyond the schema.
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?
Front-loads the purpose, then uses clear labels 参数/返回/注意 for parameters, return values, and caveats. No wasted sentences; every part adds useful information.
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 no output schema and no annotations, the description helpfully lists return fields (sessionId, content, usageStatus) and quota caveats. It stops short of distinguishing sibling tools or explaining error/quota-exhaustion behavior, so it is solid but not fully complete.
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% for the single keyword parameter, and the description adds no meaning beyond the schema; it merely restates that keyword is required with the same example. Baseline 3 applies.
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 verb+resource: 发起法规查询, and explains it searches a self-built legal database and generates an answer with legal provisions. It is clear but does not distinguish itself from siblings such as lawbotter_legal_consult or lawbotter_regulations_search.
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?
Mentions sessionId can be used with lawbotter_followup for follow-up questions and notes anonymous quota limits, but gives no explicit criteria for choosing this tool over the other legal-query siblings, nor any when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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