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kevynf

AKBridge MCP Server

by kevynf

macro_china_shibor_all

Read-onlyIdempotent

Retrieve Shanghai banking interbank lending rate reports from 2017-03-17 to present, returning current values (%) as a pandas DataFrame for China macro analysis.

Instructions

上海银行业同业拆借报告,数据区间从20170317-至今 https://datacenter.jin10.com/reportType/dc_shibor https://cdn.jin10.com/dc/reports/dc_shibor_all.js?v=1578755058 :return: 上海银行业同业拆借报告-今值(%) :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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?

The annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds only the data coverage range and a return type, without disclosing update frequency, rate limits, or data limitations.

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

Conciseness3/5

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

The core purpose is front-loaded in the first clause, but the description then includes two long source URLs and a redundant return-type line. These metadata lines do not help an agent invoke the tool and add clutter, though the overall length remains moderate.

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 description should clarify what the tool returns. It only states ':return: 上海银行业同业拆借报告-今值(%)' and ':rtype: pandas.DataFrame', which is a partial hint but does not describe the actual DataFrame columns or update cadence. The absence of parameters and annotations eases the burden, but the return shape remains underspecified.

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 tool has zero input parameters, so there are no input semantics to explain. The mention of '今值(%)' relates to the return value rather than an input parameter. Baseline 4 applies when no parameters exist.

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 names a specific resource, the Shanghai banking interbank lending report, and provides its temporal coverage (20170317-present). This is clearer than a verb-less noun phrase alone, but it does not explicitly distinguish itself from related macro rate tools such as rate_interbank or macro_china_swap_rate, leaving sibling differentiation to the tool name.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternatives are mentioned. The description only supplies the report subject, data range, and source URLs, leaving the agent to infer that this tool should be used for SHIBOR data.

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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