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kevynf

AKBridge MCP Server

by kevynf

bond_composite_index_cbond

Read-onlyIdempotent

Fetch ChinaBond composite bond index indicators (price, yield, duration, return) for selected maturity buckets.

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-综合指数 https://yield.chinabond.com.cn/cbweb-mn/indices/single_index_query :param indicator: choice of {"全价", "净价", "财富", "平均市值法久期", "平均现金流法久期", "平均市值法凸性", "平均现金流法凸性", "平均现金流法到期收益率", "平均市值法到期收益率", "平均基点价值", "平均待偿期", "平均派息率", "指数上日总市值", "财富指数涨跌幅", "全价指数涨跌幅", "净价指数涨跌幅", "现券结算量"} :type indicator: str :param period: choice of {"总值", "1年以下", "1-3年", "3-5年", "5-7年", "7-10年", "10年以上", "0-3个月", "3-6个月", "6-9个月", "9-12个月", "0-6个月", "6-12个月"} :type period: str :return: 新综合指数 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNo总值
indicatorNo财富
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, covering the safety profile. The description adds that it returns a pandas DataFrame of the composite index, but it does not disclose additional behavioral traits such as data coverage, update frequency, or output structure.

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 well-structured with a title, URL, and param/return documentation. Although the parameter lists make it lengthy, each entry is necessary. It is front-loaded with the index name and source.

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?

Without an output schema, the description should explain the return structure in more detail. It only says '新综合指数' (new composite index) and rtype pandas.DataFrame, leaving the DataFrame columns and their meaning vague. Parameter coverage is thorough, but the return value semantics are under-specified.

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

Parameters5/5

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

The input schema has two string parameters with defaults but no descriptions or enums. The description fully compensates by listing all valid choices for both indicator (17 options) and period (14 options), making it clear what values are accepted and what each represents.

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

Purpose5/5

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

The description clearly identifies the exact target as the ChinaBond Composite Index (中债-综合指数), including the source URL and hierarchy. This distinguishes it from sibling bond index tools like bond_index_general_cbond and bond_new_composite_index_cbond.

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 implies usage for retrieving the ChinaBond Composite Index through its title and parameter documentation, but it does not explicitly state when to use this tool versus alternatives, nor does it provide any exclusions or context about preferability.

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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