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kevynf

AKBridge MCP Server

by kevynf

macro_usa_cftc_merchant_currency_holding

Read-onlyIdempotent

Fetch US CFTC forex commercial holdings data from 1986 to present, returning a pandas DataFrame for market positioning analysis.

Instructions

美国商品期货交易委员会CFTC外汇类商业持仓报告,数据区间从 19860115-至今 https://datacenter.jin10.com/reportType/dc_cftc_merchant_currency :return: 美国商品期货交易委员会CFTC外汇类商业持仓报告 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

B3.4/5.0
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 fully covered structurally. The description adds the historical coverage window (19860115-present) and a source URL, which is useful context, but says nothing about update cadence or latency.

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?

It is short and front-loaded with the resource name, coverage range, and source link. The ':return:' line only restates the tool name, which is mild redundancy, but the ':rtype: pandas.DataFrame' adds return-type value.

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?

With annotations covering the safety profile and the description supplying data range, source URL, and return type, an agent has enough to invoke it correctly. Since there is no output schema, naming the pandas.DataFrame return type is the right compensating detail.

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 no parameters, so the baseline of 4 applies. There is nothing for the description to disambiguate, and it correctly implies the call is a bare fetch.

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 report — CFTC forex/currency commercial-position holdings — which is a concrete resource and distinguishes it semantically from the goods, non-commercial, and CME siblings in the tool list. It stops short of naming those siblings explicitly, so the agent must infer the distinction.

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 guidance, no exclusions, and no reference to the closer CFTC alternatives (macro_usa_cftc_nc_holding, macro_usa_cftc_merchant_goods_holding, macro_usa_cftc_c_holding). The agent is left to infer selection from the name alone.

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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