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kevynf

AKBridge MCP Server

by kevynf

index_stock_cons_csindex

Read-onlyIdempotent

Fetch constituent stocks for a given index from CSIndex. Input the index code to get the latest constituent list as structured data.

Instructions

中证指数网站-成份股目录 https://www.csindex.com.cn/zh-CN/indices/index-detail/000300 :param symbol: 指数代码,可以通过 ak.index_stock_info() 函数获取 :type symbol: str :return: 最新指数的成份股 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNo000300

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and openWorld, so the safety profile is covered. The description adds useful context beyond that — it identifies the upstream data source (CSIndex URL) and the return type/semantics ('最新指数的成份股', pandas.DataFrame) — but says nothing about rate limits, latency, or completeness of coverage.

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

Conciseness4/5

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

Purpose is front-loaded, followed by a source URL and compact param/return documentation. It is appropriately sized for a one-parameter tool, though the embedded URL and docstring-style :param/:return lines add slight structural noise without new behavioral content.

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

Completeness4/5

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

No output schema exists, and the description compensates by stating the return is a pandas.DataFrame of the latest index constituents. Combined with the annotated safety profile and the explained parameter, an agent has enough to call it correctly; only routing guidance against sibling constituent tools is missing.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry the parameter meaning, and it does: 'symbol' is defined as the index code (指数代码) and a concrete way to obtain it is given via ak.index_stock_info(). This is meaningful semantics beyond the bare schema default of '000300'.

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 description names a specific source and resource: '中证指数网站-成份股目录' (CSIndex website – constituent stock directory), which tells an agent this retrieves index constituents from CSIndex. It does not explicitly differentiate from close siblings like index_stock_cons or index_stock_cons_weight_csindex, but the stated source makes the scope clear enough to distinguish it.

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?

The only guidance is how to obtain the input value ('可以通过 ak.index_stock_info() 函数获取'), which is parameter-acquisition help rather than when-to-use guidance. There is no statement of when to prefer this over sibling constituent tools (index_stock_cons, index_stock_cons_sina, index_stock_cons_weight_csindex) or any exclusions.

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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