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kevynf

AKBridge MCP Server

by kevynf

macro_china_m2_yearly

Read-onlyIdempotent

Fetch China's annual M2 money supply data from 1998 onward for macroeconomic and monetary trend analysis.

Instructions

中国年度 M2 数据,数据区间从 19980201-至今 https://datacenter.jin10.com/reportType/dc_chinese_m2_money_supply_yoy :return: 中国年度 M2 数据 :return: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds two genuinely useful facts beyond that: the data range (19980201–present) and the return type (pandas.DataFrame), though it does not say whether values are YoY growth or level, despite the source URL suggesting yoy.

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?

The description is short and front-loads the purpose and date range. However, the duplicated ':return:' lines (restating 'China annual M2 data' plus the DataFrame type) and the raw URL add redundancy that a single return statement would have covered.

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?

For a no-parameter, read-only data-fetch tool with annotations covering safety and no output schema, the description supplies the key missing pieces: the subject, the temporal coverage, and the return container. The remaining gap is not clarifying YoY-vs-level semantics, which matters given the sibling money-supply tools.

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 and schema coverage is 100%, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly does not invent parameter semantics.

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 identifies the resource (China annual M2 data) and the coverage window (19980201–present), but it uses no verb and essentially restates the tool name and title. It does not distinguish this from closely named siblings such as macro_china_money_supply or macro_china_supply_of_money, leaving overlap unresolved.

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 the tool sitting among dozens of macro_* series with overlapping money-supply semantics. The only mildly useful context is the stated data range, which implies historical-only coverage.

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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