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kevynf

AKBridge MCP Server

by kevynf

futures_inventory_99

Read-onlyIdempotent

Fetch commodity inventory data for a specified futures symbol, such as Dalian Commodity Exchange's No.1 Soybean, from 99qh.com as a pandas DataFrame.

Instructions

99 期货网-大宗商品库存数据 https://www.99qh.com/data/stockIn?productId=12 :param symbol: 交易所对应的具体品种;如:大连商品交易所的 豆一 :type symbol: str :return: 大宗商品库存数据 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNo豆一

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, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the return type pandas.DataFrame and the data source URL, but does not describe authentication, rate limits, pagination, or output columns.

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 source and dataset name before the parameter details. The URL and Sphinx-style tags are somewhat raw but still compact, with little wasted text.

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 simple one-parameter read-only data tool with no output schema, the description supplies the return type and symbol semantics. However, it omits valid symbol lists, output structure, and any caveats about the returned DataFrame, so an agent still lacks complete invocation context.

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

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for the single optional symbol parameter. The description compensates by explaining that symbol means the specific variety for an exchange, with the example 豆一 from 大连商品交易所, but it does not list valid values or explain the productId mapping seen in the URL.

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 identifies a specific resource and source: 99期货网-大宗商品库存数据, with a URL to the source endpoint. It is clear enough to distinguish data from this provider, but it does not explicitly differentiate itself from sibling inventory tools such as futures_inventory_em beyond naming the source.

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?

The description gives no guidance on when to use this tool versus alternatives such as futures_inventory_em or other futures data tools. It only documents a source URL and parameter example, leaving usage context to inference.

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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