stock_conceptsRetrieve concept tags for any stock and view daily strength rankings of all market concept sectors, using Eastmoney data to identify leading stocks.
获取个股所属概念标签（概念板块领涨股名称匹配）及全市场概念板块当日强弱榜。东财概念板块优先
| Name | Required | Description | Default |
|---|---|---|---|
| market | No | 市场: sh=沪, sz=深, bj=京 | sh |
| symbol | Yes | 6位股票代码，如 600519 |
| 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?
With no annotations, the description carries the behavioral disclosure burden. It does disclose a data-source preference ('东财概念板块优先'), which is useful. However, it does not clarify the meaning of '概念板块领涨股名称匹配' or disclose limitations such as refresh timing or coverage gaps. It is clearly a read-only get operation from the verb '获取'.
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 sentence, front-loaded with the main purpose and free of filler. The parenthetical about leading-stock name matching is awkward but does not seriously hurt readability.
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 the output schema exists, the description does not need to explain return values. However, the description is terse about two distinct outputs and the puzzling '名称匹配' criterion. More context on how the market parameter applies and how the strength ranking relates to the individual stock would improve completeness.
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. The description does not add parameter-specific meaning beyond the schema; it does not explain how 'market' affects the output or how the symbol maps to concept tags. It merely restates the overall purpose.
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 a clear verb ('获取') and two concrete deliverables: the stock's concept tags and the full-market concept-sector strength ranking. It is distinct enough from siblings, though the parenthetical '概念板块领涨股名称匹配' adds ambiguity about the matching method.
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?
Intended usage is implied by the deliverables: an agent would call this when it needs a stock's concept tags or the day's concept-sector strength ranking. However, there is no explicit when-to-use guidance, exclusions, or alternatives compared with similar sibling tools like sector_rotation or industry_themes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.