Get the Shenwan industry tree across three levels, including valuation data. Use this to navigate industry classifications and access key metrics.
申万三级行业树（31一级→131二级→336三级），含估值数据
| Name | Required | Description | Default |
|---|---|---|---|
| 展开 | No | ||
| 深度 | No | ||
| 行业 | 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?
Since no annotations are provided, the description carries the behavioral disclosure burden. It adds useful content-level context by stating the exact hierarchy sizes and the inclusion of valuation data, but it does not explain how the returned tree is shaped by the 展开/深度/行业 parameters or whether valuation appears at every level.
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 a single dense sentence with no wasted words. It front-loads the core resource and then adds the most useful precision: the exact number of levels and the valuation-data context.
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?
Even with an output schema present, the description is incomplete for practical use: it omits parameter behavior, gives no selection criteria among many industry-related siblings, and does not clarify what '估值数据' includes. The defaults allow a blind call, but an agent cannot make an informed choice or customize the query from this description alone.
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?
The input schema has 0% description coverage, and the description never mentions the parameters 展开, 深度, or 行业. The hierarchy counts indirectly hint that 深度 relates to tree levels, but the filter/expansion semantics of the other parameters are left entirely to inference.
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 clearly identifies the resource: a Shenwan three-level industry tree with explicit level counts (31 → 131 → 336) and valuation data. It is informative enough to distinguish it from most siblings, though it lacks an explicit verb and does not directly contrast it with similar industry tools.
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?
No guidance is given for when to use this tool versus alternatives such as industry_sw_constituents, industry_classify, industry_quotes, or industry_sw_daily. There are no conditions, exclusions, or context cues to help an agent decide between this tree and its industry-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.