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kevynf

AKBridge MCP Server

by kevynf

amac_fund_info

Read-onlyIdempotent

Retrieve private fund manager fund product information from AMAC's public disclosure by specifying start and end pages, returning structured data for analysis.

Instructions

中国证券投资基金业协会-信息公示-基金产品-私募基金管理人基金产品 https://gs.amac.org.cn/amac-infodisc/res/pof/fund/index.html :param start_page: 开始页码,获取指定页码直接的数据 :type start_page: str :param end_page: 结束页码,获取指定页码直接的数据 :type end_page: str :return: 私募基金管理人基金产品 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_pageNo2000
start_pageNo1

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true and destructiveHint=false, so safety is covered. The description adds that this is a page-range scrape of an external website returning a pandas.DataFrame, but says nothing about rate limits, scrape slowness, or reliability.

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?

It is a pasted Sphinx docstring: the first line duplicates the annotation title, then the URL, then per-parameter directives. Front-loaded and not bloated, but structurally redundant against the title and marginally wasteful.

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?

The description states the return type (:rtype: pandas.DataFrame), which is useful since there is no output schema. However, it does not describe what columns/content the DataFrame holds or how paging interacts with the defaults, leaving moderate gaps for a data-retrieval tool.

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 burden, and it does document both parameters (start_page = starting page number, end_page = ending page number). It could be stronger by clarifying that the two define a range (the Chinese text is ambiguous, reading as 'data of the specified page').

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 the source (AMAC), the disclosure section, and the specific resource ('私募基金管理人基金产品' / private fund manager fund products), so an agent knows it lists fund products from the AMAC disclosure portal. It does not, however, differentiate itself from the many other amac_* siblings (e.g. amac_fund_abs, amac_fund_sub_info).

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?

No when-to-use or when-not-to-use guidance is provided. With 13+ sibling amac_* tools and hundreds of other data tools, the description gives no basis for choosing this one over alternatives.

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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