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Glama

QuantSonar

by io.github.QuantSonar

dividend

分红送股（分红送股） 需要 PRO 及以上套餐（低档位调用返回 403）。

Args: symbol: 证券代码（带后缀），如 000001.SZ start_date: 起始日期 YYYYMMDD end_date: 结束日期 YYYYMMDD record_date: 股权登记日 YYYYMMDD ex_date: 除权除息日 YYYYMMDD imp_ann_date: 实施公告日 YYYYMMDD

Returns: JSON 数组；字段: symbol, end_date, ann_date, div_proc, stk_div, stk_bo_rate, stk_co_rate, cash_div, cash_div_tax, record_date, ex_date, pay_date, div_listdate, imp_ann_date

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNo证券代码（带后缀），如 000001.SZ
ex_dateNo除权除息日 YYYYMMDD
end_dateNo结束日期 YYYYMMDD
start_dateNo起始日期 YYYYMMDD
record_dateNo股权登记日 YYYYMMDD
imp_ann_dateNo实施公告日 YYYYMMDD

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description adds the PRO requirement, 403 behavior, and return format, but does not explicitly state read-only semantics or other side effects.

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?

Structured Args/Returns with clear sections and no filler beyond a repeated title phrase; the PRO requirement is front-loaded.

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 description is adequate for a straightforward query tool and includes access requirements and return fields, but lacks parameter combination guidance and doesn't compensate for the absence of annotations.

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?

Schema coverage is 100%, so the baseline is 3. The description merely repeats the schema parameter descriptions without adding relationships, required combinations, or format constraints.

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 identifies the resource (dividend/bonus share data) and enumerates return fields, making the tool's function inferable. However, it lacks an explicit verb like 'query' or 'retrieve' and does not distinguish from sibling tools such as 'distribution'.

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?

Only a PRO tier requirement and 403 error are mentioned; no guidance on when to prefer this tool over alternatives or how to combine parameters.

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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TDQS

B3.3/5.0
Disambiguation3/5

Several tools have overlapping purposes or unclear names, such as daily vs etf_daily vs index_daily vs fx_daily, and fundamentals vs technical_factors_pro (which also includes PE/PB). top_inst and top_list are also easily confused. Descriptions help, but the names alone are not always sufficient to distinguish them.

Naming Consistency3/5

All names use lowercase with underscores, which is consistent, but there is variation in number (daily vs stocks), specificity (daily vs index_daily), and verbosity (top_inst vs top_list). The pattern is not uniform across the set, making it less predictable.

Tool Count3/5

45 tools is on the heavy side for an MCP server, and there is redundancy (technical_factors and technical_factors_pro overlap significantly). For a broad financial data API, the count is justifiable, but it borders on overwhelming.

Completeness4/5

The tool set covers a wide range of financial data: quotes, fundamentals, technicals, financial statements, corporate actions, money flows, ETF data, index data, and news. There are minor gaps (e.g., no bond data) but the core domain of Chinese A-share/ETF/FX data is well covered.

Resources