Search China's customer-service compliance Q&A by keyword to return relevant entries with brief answers. Use it to look up rules on topics like escalation or filing.
按关键词检索合规问答，返回最相关的若干条（含简要答案）。
Args:
query: 检索词，如「转人工」「备案 登记」「知识库 切分」
top_k: 返回条数，默认 5
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| top_k | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds useful behavioral context: results are ranked by relevance and contain brief answers rather than full text. No contradiction with annotations.
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-structured: a single front-loaded purpose sentence followed by a short Args block with examples. Every sentence earns its place; there is no filler or redundant restatement.
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?
With only two simple parameters, annotations covering safety, and an output schema present, the description covers purpose, parameter semantics, and result form (most relevant items with brief answers). Nothing critical for correct invocation is missing.
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 0%, so the description carries the full burden. It fully documents both parameters: query is explained as the search term with three concrete examples, and top_k is defined as the number of results with a default of 5. This adds meaning well beyond the bare schema types.
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 ('检索'/'search') and resource ('合规问答'/'compliance Q&A'), and states that it returns the most relevant results with brief answers. This clearly identifies what the tool does and implicitly distinguishes it from siblings like get_answer (single answer) and list_questions (list questions).
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 gives a clear usage context—keyword-based search of compliance Q&A—so an agent can infer when to invoke it. However, it does not explicitly name alternative tools or state when not to use it, so it lacks explicit exclusions/sibling routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.