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Python
Hybrid

qhkc_tool_gdp

Read-onlyIdempotent

Fetch current GDP and regional economic indicators, including growth, debt, budget, and population, as structured data. Use for real-time country comparisons, not historical trends.

Instructions

奇货可查-工具-各地区经济数据 实时更新数据，暂不能查询历史数据 :param url: :return: pandas.DataFrame 国家 国内生产总值 国内生产总值YoY 国内生产总值QoQ ... 预算 债务 经常账户 人口 美国 20494 2.30% 2.00% ... -3.80% 106.10% -2.40 327.17 欧元区 13670 1.20% 0.20% ... -0.50% 85.10% 2.90 341.15 中国 13608 6.20% 1.60% ... -4.20% 50.50% 0.40 1395.38 日本 4971 1.00% 0.30% ... -3.80% 238.20% 3.50 126.25 德国 3997 0.40% -0.10% ... 1.70% 60.90% 7.30 82.85 英国 2825 1.30% -0.20% ... -2.00% 84.70% -3.90 66.19 法国 2778 1.40% 0.30% ... -2.50% 98.40% -0.30 67.19 印度 2726 5.00% 1.00% ... -3.42% 68.30% -2.30 1298.04 意大利 2074 -0.10% 0.00% ... -2.10% 134.80% 2.50 60.48 巴西 1869 1.00% 0.40% ... -7.10% 77.22% -0.77 208.49 加拿大 1709 1.60% 0.90% ... -0.70% 90.60% -2.60 37.31 俄罗斯 1658 0.90% 0.20% ... 2.70% 13.50% 7.00 146.90 韩国 1619 2.00% 1.00% ... -1.60% 36.60% 4.70 51.61 澳大利亚 1432 1.40% 0.50% ... -0.60% 40.70% -1.50 25.18 西班牙 1426 2.00% 0.40% ... -2.50% 97.10% 0.90 46.66 墨西哥 1224 -0.80% 0.00% ... -2.00% 46.00% -1.80 125.33 印尼 1042 5.05% 4.20% ... -1.76% 29.80% -3.00 264.20 荷兰 913 1.80% 0.40% ... 1.50% 52.40% 10.80 17.12 沙特阿拉伯 782 0.50% 0.00% ... -9.20% 19.10% 9.20 33.41 土耳其 767 -1.50% 1.20% ... -2.00% 30.40% -3.50 82.00 瑞士 706 0.20% 0.30% ... 1.30% 27.70% 10.20 8.48 台湾 589 2.40% 0.67% ... -1.90% 30.90% 11.60 23.58 波兰 586 4.50% 0.80% ... -0.40% 48.90% -0.70 37.98 瑞典 551 1.00% 0.10% ... 0.90% 38.80% 2.00 10.12 比利时 532 1.20% 0.20% ... -0.70% 102.00% -1.30 11.41 阿根廷 519 0.60% -0.30% ... -5.50% 86.20% -5.40 44.50 泰国 505 2.30% 0.60% ... -2.50% 41.80% 7.50 66.41 委内瑞拉 482 -22.50% -5.40% ... -20.00% 23.00% 6.00 31.83 奥地利 456 1.50% 0.30% ... 0.10% 73.80% 2.30 8.82 伊朗 454 1.80% NaN ... -3.90% 44.20% 1.30 82.10 挪威 435 -0.70% 0.30% ... 7.30% 36.30% 8.10 5.30 阿联酋 414 2.20% 1.70% ... -1.80% 18.60% 9.10 9.60 尼日利亚 397 1.94% 2.85% ... -2.80% 18.20% 2.30 195.87 爱尔兰 376 5.80% 0.70% ... 0.00% 64.80% 9.10 4.84 以色列 370 3.20% 0.30% ... -1.90% 61.00% 1.90 8.97 南非 366 0.90% 3.10% ... -4.40% 55.80% -3.60 58.78 新加坡 364 0.10% -3.30% ... 0.40% 112.20% 17.70 5.64 香港 363 0.50% -0.40% ... 2.10% 38.40% 4.30 7.48 马来西亚 354 4.90% 1.00% ... -3.70% 51.80% 2.30 32.40 丹麦 351 2.60% 0.90% ... 0.50% 34.10% 6.10 5.78 菲律宾 331 5.50% 1.40% ... -3.20% 41.90% -2.40 107.00 哥伦比亚 330 3.00% 1.40% ... -3.10% 50.50% -3.80 49.83 巴基斯坦 313 5.20% 5.79% ... -6.60% 72.50% -4.80 212.22 智利 298 1.90% 0.80% ... -1.70% 25.60% -3.10 18.75 芬兰 276 1.20% 0.50% ... -0.70% 58.90% -1.90 5.51 孟加拉国 274 7.90% 7.90% ... -4.80% 27.90% -3.60 163.70 埃及 251 5.70% 5.40% ... -8.20% 90.50% -2.40 98.00 越南 245 7.31% 6.88% ... -3.50% 57.50% 3.00 94.67 捷克共和国 244 2.70% 0.70% ... 0.90% 32.70% 0.30 10.61

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNohttps://qhkch.com/dist/views/toolbox/gdp.html?v=1.10.7.1

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

C2.8/5.0
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 covered. The description usefully adds the real-time-only/no-history limitation, but says nothing about the url parameter's role, rate limits, or data provenance.

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 definition front-loads the useful note (real-time, no history) but then dumps roughly fifty rows of sample tabular data, which dominates the text and buries the actionable information. The bulk is far larger than needed to convey the tool's purpose.

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?

With no output schema, the sample table does helpfully reveal the return column structure and units (GDP, YoY, QoQ, budget, debt, current account, population). But the url parameter is left unexplained and there is no reference to how this differs from the numerous macro_* GDP tools, leaving meaningful gaps.

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?

Schema coverage is 0% and the single url parameter has only a default value in the schema. The description's ':param url:' line adds no meaning at all, and the giant data sample does not explain what the url is used for. With 1 undocumented parameter the description falls short of the zero-param baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the resource (各地区经济数据, i.e. economic data by country/region) and notes it is real-time and not historical, so an agent can tell roughly what it returns. However it never states the verb explicitly (a retrieval/query operation) and gives no differentiation from the many macro_* GDP siblings such as macro_china_gdp or macro_china_gdp_yearly.

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 line '实时更新数据，暂不能查询历史数据' conveys a partial when-not condition (no historical queries) that the agent can act on. But it offers no positive when-to-use guidance and never mentions the alternative macro/GDP tools an agent should weigh against it.

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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