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kevynf

AKBridge MCP Server

by kevynf

bond_new_composite_index_cbond

Read-onlyIdempotent

Fetches ChinaBond New Composite Index data for specified indicators and maturity periods, providing key metrics like yields, durations, and transaction amounts for bond market analysis.

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-新综合指数 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, so the safety profile is covered. The description adds the data source URL and the index hierarchy, which gives context about the data origin. However, it does not disclose behaviors like rate limits, pagination, date range coverage, or network dependency, leaving some gaps beyond what annotations provide.

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 line breaks separating the source, parameters, and return information. It is not overly verbose, though the first line repeats the hierarchical name which also appears in the annotations' title. The parameter lists are essential and formatted compactly. Overall, it is efficient and readable.

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 tool is relatively simple with two optional parameters and no output schema. The description states the return type (pandas DataFrame) and the return value (新综合指数), but does not detail the DataFrame's columns, the time range of data, or how parameters affect the output. Annotations cover safety, but for a complete understanding, more behavioral and output context would be helpful. It is minimally adequate.

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 schema provides only parameter names with defaults and no descriptions (0% schema coverage). The description compensates exceptionally by listing all valid choices for both indicator and period, which are critical for correct invocation. It does not explain the meaning of each choice, but the labels are self-explanatory in context. This adds significant value beyond the bare schema.

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 identifies the specific resource: 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-新综合指数, along with a URL. The return type and value are also specified, making the tool's purpose evident. However, it lacks an explicit action verb like 'fetch' or 'query', but the context implies data retrieval, so it's clear but not perfectly articulated.

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 use this tool versus the many similar bond index tools in the sibling list (e.g., bond_composite_index_cbond, bond_treasury_index_cbond). It does not mention alternatives, exclusions, or typical use cases. The only context is the specific index name, which differentiates it somewhat, but explicit usage guidance is absent.

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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