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kevynf

AKBridge MCP Server

by kevynf

futures_inventory_99

Read-onlyIdempotent

Retrieve commodity inventory data for futures symbols from 99qh.com. Input a symbol (e.g., 豆一) to get stock levels 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
Behavior3/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds the return type (pandas.DataFrame) and the data source (99qh.com), but does not disclose other behavioral traits such as network dependence, rate limits, or response format nuances. Given the annotations, a score of 3 is appropriate.

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

Conciseness5/5

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

The description is brief, well-formatted as a docstring, and includes only essential information: source URL, parameter semantics, and return type. It is front-loaded with the tool's purpose and avoids unnecessary elaboration.

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?

Without an output schema, the description does not disclose the structure of the returned DataFrame (e.g., columns, time range). It also lacks information about data update frequency or coverage, which could be important for an agent. However, the tool is relatively simple, so the moderate completeness is acceptable.

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 schema has no description for the symbol parameter, so the description's explanation of symbol as 'the specific product variety corresponding to the exchange' with an example (DCE soybean) adds crucial meaning. However, it does not provide a comprehensive list or method for discovering valid symbols.

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 clearly identifies the tool as providing bulk commodity inventory data from 99qh.com, with a specific URL and a parameter for commodity symbol. However, it lacks an explicit verb like 'get' or 'retrieve', and it does not differentiate from sibling tools such as futures_inventory_em, though the source is distinct.

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 provides no guidance on when to use this tool versus alternatives, nor any exclusions or alternative tools. It only describes the parameter and return type, implying basic usage but not offering context for selection.

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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