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kevynf

AKBridge MCP Server

by kevynf

get_dce_rank_table

Read-onlyIdempotent

Retrieve Dalian Commodity Exchange top 20 member position rankings by date and commodity variety. Get volume, long, and short positions for market analysis.

Instructions

大连商品交易所前 20 会员持仓排名数据明细, 由于交易所网站问题, 需要 20200720 之后才有数据 注: 该交易所只公布标的合约排名 :param date: 日期 format:YYYY-MM-DD 或 YYYYMMDD 或 datetime.date 对象, 为空时为当天 :param vars_list: 合约品种如 RB、AL 等列表为空时为所有商品, 数据从 20060104 开始,每交易日 16:30 左右更新数据 :return: 持仓排名 :rtype: pandas.DataFrame

返回值格式 rank 排名 int vol_party_name 成交量排序的当前名次会员 string(中文) vol 该会员成交量 int vol_chg 该会员成交量变化量 int long_party_name 持多单排序的当前名次会员 string(中文) long_open_interest 该会员持多单 int long_open_interest_chg 该会员持多单变化量 int short_party_name 持空单排序的当前名次会员 string(中文) short_open_interest 该会员持空单 int short_open_interest_chg 该会员持空单变化量 int symbol 标的合约 string var 品种 string date 日期 string YYYYMMDD

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo20230706
vars_listNo
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing a safe read-only profile. The description adds meaningful behavioral context beyond those hints: the 20200720 data cutoff caused by exchange website issues, the limitation that the exchange only publishes underlying contract rankings, and the daily 16:30 update cadence. No contradiction with annotations exists.

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 front-loaded with a clear purpose sentence followed by caveats, parameter documentation, and a structured return-format table. The return column block is lengthy but justified since no output schema exists to carry that information. Sections are logically ordered and each part contributes useful information without redundancy.

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 2-parameter read-only tool with no output schema and 0% schema coverage, the description is highly complete: it covers purpose, data availability constraints, scope limitations, parameter formats and defaults, return type, and all 11 return columns. The main gap is the internal inconsistency between the 20200720 data cutoff and the 20060104 start date mentioned in the vars_list documentation, which leaves uncertainty about actual data availability.

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?

Schema description coverage is 0%, so the description carries the full burden of explaining both parameters. It documents date formats (YYYY-MM-DD, YYYYMMDD, datetime.date object), the default 'today' behavior, and vars_list semantics (a list of varieties, empty = all commodities). However, it does not enumerate which variety codes are valid for DCE, and its examples (RB, AL) are Shanghai Futures Exchange products, which could mislead users selecting parameters for this DCE-focused tool.

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 resource: DCE (Dalian Commodity Exchange) top 20 member position ranking details (大连商品交易所前 20 会员持仓排名数据明细). It adds a distinguishing note that the exchange only publishes underlying contract rankings. However, it does not explicitly differentiate from closely related siblings like futures_dce_position_rank or get_cffex_rank_table, relying only on the exchange name mentioned in both the tool name and description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides helpful usage context: accepted date formats, default 'today' behavior, empty vars_list meaning all commodities, and the ~16:30 daily data update schedule. However, it never states when to prefer this tool over alternatives like get_cffex_rank_table, get_shfe_rank_table, or futures_dce_position_rank, and the data availability guidance is internally inconsistent—the header says data only exists after 20200720, while the vars_list parameter says data starts from 20060104.

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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