Skip to main content
Glama
jarvislee90s-dot

local-datasource

query_convertible_bond

Fetch China convertible bond data and save to CSV. Includes market overview, bond terms, historical prices, and issuer financials.

Instructions

Query China convertible bonds. Output is written to file_path as CSV. kind=overview: 全市场一览含转股溢价率/评级/规模 (bond_zh_cov). kind=terms: 强赎/回售/下修条款+剩余期限 (集思录). kind=history: 单只转债历史K线 daily/min (bond_zh_hs_cov_daily/min). kind=issuer_finance: 发行人正股三大报表;城投/非上市发行人返回引导性提示。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesQuery type
periodNoK-line period (history)daily
symbolNoCB symbol e.g. sz128039 (history)
keywordNoKeyword filter (overview, optional)
end_dateNoEnd date YYYY-MM-DD (history)
bond_codeNoCB code (issuer_finance, mutually exclusive with stock_code)
file_pathYesOutput CSV file path
start_dateNoStart date YYYY-MM-DD (history)
stock_codeNoUnderlying stock code (issuer_finance, mutually exclusive with bond_code)
report_typeNoFinancial report type (issuer_finance)资产负债表

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

No annotations are provided, so the description carries the behavioral burden. The description discloses a non-obvious side effect: output is written to file_path as CSV, and it also handles the special issuer_finance case with a guidance prompt for municipal and non-listed issuers. It does not mention overwrite behavior or error cases, but the core behavioral traits are covered well.

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 compact and front-loaded with the main purpose and file output. Each kind clause earns its place. Some encoded Chinese text could be clearer for non-Chinese readers, but there is no redundance.

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

Completeness4/5

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

For a 10-parameter, 4-mode tool with no output schema, the description covers what each mode returns, the CSV destination, and an edge-case behavior. It does not spell out all combinations, but it provides enough context for an agent to configure required and mode-specific parameters correctly.

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?

Schema coverage is 100%, so parameters already have descriptions. The tool description still adds real value by mapping each kind to its expected content and data source, and by associating history mode with periods and symbols. This goes beyond the schema's terse field descriptions.

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 states 'Query China convertible bonds' and defines four distinct kinds (overview, terms, history, issuer_finance) with data sources and content. This is specific enough to distinguish it from siblings like query_bond and query_stock.

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 four kind values give implicit usage guidance, but the description does not explicitly state when to prefer this tool over query_bond or query_stock, nor does it give exclusion conditions. It provides clear context for this tool itself but lacks explicit alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jarvislee90s-dot/local-datasource'

If you have feedback or need assistance with the MCP directory API, please join our Discord server