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A股数据 API (A-Share Data API)

ashare_dividend

分红送转历史(每股分红/送股/除权日)。用户问'分红/股息/送转'用这个。⚠️ 要分红派息日历(哪天除权)请用 ashare_events——本工具是历史记录。只读查询;按公告披露更新。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes股票代码:sh600667
yearsNo年数(默认 3)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / code / description
      Added value: +"股票代码:sh600667"
    • addedInput schema / properties / years / description
      Added value: +"年数(默认 3)"
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden. It clearly states the tool is read-only ('只读查询') and notes the data update cadence ('按公告披露更新'), which are useful behavioral facts beyond the schema. It does not discuss rate limits or auth, but no annotations exist and these are less critical for a simple read-only tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only three sentences yet packs the core purpose, user-trigger phrases, a sibling-tool pointer, read-only status, and update frequency. Every sentence earns its place, and the key distinction from ashare_events is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter tool with full schema coverage and an output schema, the description is complete: it defines scope, distinguishes the historical nature from the calendar tool, and states behavior. No critical information needed to invoke the tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both 'code' and 'years' with examples and defaults. The description adds context about the tool being historical but does not add parameter-level meaning beyond the schema, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with '分红送转历史(每股分红/送股/除权日)', which names the exact resource (dividend/bonus share history) and the data fields it covers. It also explicitly distinguishes itself from ashare_events, so an agent can tell the two tools apart without inspecting schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It states a concrete trigger condition ('用户问"分红/股息/送转"用这个') and an explicit alternative with the condition that selects it ('要分红派息日历...请用 ashare_events'). This is clear when-to-use and 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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