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kevynf

AKBridge MCP Server

by kevynf

macro_china_new_house_price

Read-onlyIdempotent

Fetches China new house price index values for two cities, allowing analysis of regional housing price changes.

Instructions

中国-新房价指数 https://data.eastmoney.com/cjsj/newhouse.html :param city_first: 城市;城市列表见目标网站 :type city_first: str :param city_second: 城市;城市列表见目标网站 :type city_second: str :return: 新房价指数 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
city_firstNo北京
city_secondNo上海

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint and destructiveHint, so the safety profile is fully covered by structured data. The description adds the source URL and the return type (pandas.DataFrame), which is modest extra context but says nothing about freshness, coverage period, or rate limits.

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 content is short and front-loaded with the resource name and source link. However, the repeated :param/:type docstring lines add schema-redundant noise, and the final '城市列表见目标网站' pointer is vague rather than informative.

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 low-complexity two-parameter read tool with no output schema, the description covers the source and return type adequately. It still omits what the two city parameters mean in relation to each other and any usage context, leaving meaningful gaps for correct invocation.

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

Parameters2/5

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. It labels both parameters simply as '城市' and defers the allowed values to an external website, and it never explains the relationship between city_first (default 北京) and city_second (default 上海) or why two cities are input.

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 resource (中国-新房价指数, China new-house price index) and cites the exact data source URL, so an agent knows what data it yields. It does not explicitly differentiate itself from nearby siblings such as macro_china_real_estate or macro_usa_house_price_index, so it stops short of a 5.

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 statement of when to use this tool versus alternatives, and no prerequisites or exclusions. The only guidance is 'see the target website for the city list,' which is a parameter hint rather than usage context.

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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