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kevynf

AKBridge MCP Server

by kevynf

stock_circulate_stock_holder

Read-onlyIdempotent

Fetches circulating shareholder data for a given stock symbol from Sina Finance, returning up to the top five holders as a pandas DataFrame for shareholder analysis.

Instructions

新浪财经-股东股本-流通股东 P.S. 特定股票特定时间只有前 5 个;e.g., 000002 https://vip.stock.finance.sina.com.cn/corp/go.php/vCI_CirculateStockHolder/stockid/600000.phtml :param symbol: 股票代码 :type symbol: str :return: 新浪财经-股东股本-流通股东 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNo600000

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and non-destructive, so the safety profile is covered. The description adds one genuinely useful behavioral fact beyond them: only the top 5 shareholders are returned for a given stock/date, which sets expectations about truncation. It says nothing about whether data is latest-only or historical, or about rate limiting.

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

Conciseness3/5

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

The tool's actual identity is front-loaded, but the entry is padded with an example URL and Sphinx-style ':param/:type/:return/:rtype' boilerplate whose return line simply restates the title. There is redundancy rather than bloat, so it is tolerable but not efficient.

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

Completeness3/5

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

For a single-parameter read tool with no output schema, the description should at least say what the returned DataFrame contains; it only names the same section label plus 'pandas.DataFrame'. The top-5 limitation is helpful, but column semantics and temporal scope are left unspecified.

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?

With schema description coverage at 0%, the description carries the burden and only partly discharges it: ':param symbol: 股票代码' confirms the parameter is an A-share ticker, and the embedded examples (000002, 600000 and the 600000.phtml URL) imply a 6-digit numeric format that the schema's bare string type with default '600000' does not spell out. Useful but minimal.

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

Purpose4/5

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

The first line plus the example URL identify a specific resource: the circulating/tradable shareholder register of a given A-share, scraped from Sina Finance. That is more specific than a bare label, but the description never distinguishes this from close siblings such as stock_main_stock_holder, stock_fund_stock_holder, or the gdfx holder tools, so routing still requires name inference.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance and no named alternative, despite many neighbouring shareholder/holding-ratio tools in the sibling list. The only contextual hint is the P.S. that data is limited to the top 5 holders per stock per period, which is a data constraint rather than usage direction.

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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