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kevynf

AKBridge MCP Server

by kevynf

get_qhkc_fund_bs

Read-onlyIdempotent

Retrieve futures net position distribution from Qihuo Kecha for a given date, showing each contract's net value and ratio to assess market sentiment.

Instructions

奇货可查-资金-净持仓分布 可获取数据的时间段为:"2016-10-10:2019-09-30" :param url: 网址 :param date: 中文名称 :return: 净持仓分布 :rtype: pandas.DataFrame symbol_df name value ratio date IC 1552535406 0.195622 20190924 IF 536644080 0.0676182 20190924 橡胶 536439921 0.0675924 20190924 沪铜 460851099 0.0580681 20190924 豆粕 401005794 0.0505275 20190924 螺纹钢 329159263 0.0414747 20190924 焦炭 325646968 0.0410321 20190924 燃料油 313246789 0.0394697 20190924 IH 245556750 0.0309406 20190924 棉花 214538541 0.0270323 20190924 PTA 206340552 0.0259993 20190924 白糖 139901255 0.0176278 20190924 豆油 133664010 0.0168419 20190924 沪铝 109789864 0.0138337 20190924 沪锌 107440906 0.0135378 20190924 纸浆 95517374 0.0120354 20190924 苹果 81058733 0.0102136 20190924 塑料 63665245 0.00802194 20190924 菜油 61544593 0.00775474 20190924 铁矿石 60751108 0.00765475 20190924 焦煤 58327920 0.00734943 20190924 甲醇 52148752 0.00657084 20190924 沥青 49207374 0.00620022 20190924 菜粕 48266258 0.00608164 20190924 棕榈油 31615548 0.00398362 20190924 PP 29374826 0.00370128 20190924 豆一 22368376 0.00281846 20190924 玉米 13861567 0.00174658 20190924 沪锡 7485903 0.000943238 20190924 淀粉 4811234 0.000606225 20190924 棉纱 3627240 0.000457039 20190924 尿素 2290674 0.000288629 20190924 鸡蛋 2035406 0.000256465 20190924 粳米 1999282 0.000251913 20190924 油菜籽 533482 6.72197e-05 20190924 晚籼稻 0 0 20190924 强麦 0 0 20190924 沪铅 89914 1.13293e-05 20190924 豆二 379200 4.77799e-05 20190924 硅铁 5025872 0.000633269 20190924 红枣 8521668 0.00107375 20190924 锰硅 9472832 0.00119359 20190924 郑煤 9888272 0.00124594 20190924 乙二醇 18324242 0.00230889 20190924 PVC 19454830 0.00245135 20190924 玻璃 27076226 0.00341166 20190924 热卷 28832929 0.003633 20190924 沪银 375076371 0.0472603 20190924 沪镍 411622624 0.0518652 20190924 沪金 719371823 0.0906422 20190924

long_short_df name value ratio date 空 6303252093 0.794222 20190924 多 1633136803 0.205778 20190924

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNohttps://qhkch.com/ajax/fund_bs_pie.php
dateNo20190924
Behavior4/5

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

The description adds the available time window and the output structure (symbol_df and long_short_df), which goes beyond the annotations. It also provides sample data to illustrate the return format. There is no contradiction with the read-only, idempotent, and open-world annotations.

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

Conciseness2/5

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

The description is bloated with a large sample output (over 50 lines), while the actual guidance is minimal. The critical information (what, when, parameters) is mixed with huge data tables, making it hard to scan quickly.

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?

The description does explain the return value (pandas DataFrame with symbol_df and long_short_df) and provides sample data, which is helpful given the lack of an output schema. However, the parameter descriptions are inadequate, and it doesn't clarify the exact date format or handling of out-of-range dates. For a simple tool, this is middling.

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

Parameters2/5

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

The input schema has no descriptions (0% coverage), so the description must clarify parameters. It lists 'url: 网址' and 'date: 中文名称', but the latter is vague and likely erroneous ('Chinese name' instead of 'date'). The date format is only inferable from the sample output, which is insufficient.

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 names the resource ('净持仓分布' = net position distribution) and indicates this is a data retrieval function for that specific dataset from Qihuo Kechacha. The specific resource is named, but it does not explicitly differentiate from sibling tools like get_qhkc_fund_position or get_qhkc_fund_money_change.

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 choose this tool over alternatives. It mentions an available date range (2016-10-10 to 2019-09-30) which acts as a constraint, but there is no explicit recommendation, exclusion, or comparison with sibling tools.

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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