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kevynf

AKBridge MCP Server

by kevynf

macro_china_imports_yoy

Read-onlyIdempotent

Retrieve China's import year-over-year growth rate in USD from 1996 to present for macroeconomic analysis and trade monitoring.

Instructions

中国以美元计算进口年率报告,数据区间从 19960201-至今 https://datacenter.jin10.com/reportType/dc_chinese_imports_yoy https://cdn.jin10.com/dc/reports/dc_chinese_imports_yoy_all.js?v=1578754588 :return: 中国以美元计算进口年率报告 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds the historical coverage window (19960201 to present), which is genuinely useful behavioral context, but it does not describe return shape, update cadence, or data source reliability beyond raw URLs.

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

Conciseness2/5

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

Two raw URLs and a repeated ':return:' line that simply restates the resource name pad the description without adding decision-relevant information. The signal (resources + coverage window) is there but buried under non-functional noise.

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 zero-parameter read-only report tool with annotations covering safety and no output schema, the description plus annotations are minimally sufficient. However, it says nothing about the return columns or units beyond 'imports YoY in USD', leaving the agent to guess what the DataFrame contains.

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?

The tool takes zero parameters, which is the baseline-4 case. The description implicitly confirms there is nothing to configure by presenting the tool as a fixed report, consistent with the empty schema and required=0.

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

Purpose3/5

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

The description names the resource (China's imports YoY report in USD) and the date range, which identifies the tool. But with dozens of near-identical macro_china_* siblings (exports_yoy, cpi_yearly, ppi_yearly, etc.), it offers no explicit differentiation beyond the resource name itself, so an agent must infer from the name rather than the description.

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 the many adjacent macro siblings such as macro_china_exports_yoy or macro_china_trade_balance. The only contextual cue is the embedded data range and URLs, which is not usage 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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