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kevynf

AKBridge MCP Server

by kevynf

bond_treasury_index_cbond

Read-onlyIdempotent

Retrieve ChinaBond treasury index data by selecting indicator (full, clean, or wealth price) and maturity period. Returns the index series as a DataFrame.

Instructions

中国债券信息网-中债指数-中债指数族系-总指数-综合类指数-中债-国债指数 https://yield.chinabond.com.cn/cbweb-mn/indices/single_index_query :param indicator: choice of {"全价", "净价", "财富"} :type indicator: str :param period: choice of {'0-1Y', '0-3Y', '0-5Y', '0-10Y', '1-3Y', '1-5Y', '1-10Y', '3-5Y', '5Y', '7Y', '7-10Y', '10Y', '30Y'} :type period: str :return: 国债指数 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNo5Y
indicatorNo财富
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds the data source URL and output type (pandas.DataFrame) but no additional behavioral details such as pagination, rate limits, or data coverage. 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.

Conciseness3/5

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

The description is relatively compact but front-loads a verbose source path and URL that are not essential for invoking the tool. The parameter and return documentation are useful, yet the overall structure reads as a docstring rather than a purpose-driven description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has two parameters and no output schema, so the description should clarify output columns, date coverage, and uniqueness among siblings. It only states the return is a 国债指数 (treasury bond index) DataFrame, which is insufficient for an agent to understand the data without additional inspection.

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

Parameters3/5

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

The schema has zero description coverage for parameters, so the description must compensate. It lists allowed values for indicator (full price, net price, wealth) and period (various maturity ranges), which is helpful, but it does not explain the meaning of each indicator or the structure of the returned data. This is partial compensation but leaves semantic gaps.

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 consists of a Chinese source path and return type with no explicit verb, so it only implies the tool retrieves the ChinaBond Treasury Bond Index. It names the resource precisely but does not explicitly state the operation or differentiate it from sibling bond index tools like bond_composite_index_cbond or bond_index_general_cbond.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool versus alternatives. Sibling tools include multiple bond index tools, but the description provides no selection criteria, exclusions, or context to help an agent choose this specific treasury index tool.

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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