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Glama

technical_factors

技术面因子(行情数据) 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 trade_date: 单个交易日 YYYYMMDD(与 start/end 二选一)

Returns: JSON 数组;字段: symbol, trade_date, open_hfq, close_hfq, high_hfq, low_hfq, pre_close_hfq, open_qfq, close_qfq, high_qfq, low_qfq, pre_close_qfq, adj_factor, macd_dif, macd_dea, macd, kdj_k, kdj_d, kdj_j, rsi_6, rsi_12, rsi_24, boll_upper, boll_mid, boll_lower, cci

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNo证券代码(带后缀),如 000001.SZ
end_dateNo结束日期 YYYYMMDD
start_dateNo起始日期 YYYYMMDD
trade_dateNo单个交易日 YYYYMMDD(与 start/end 二选一)

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

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the burden. It discloses the 403 error for lower tiers and enumerates all output fields, which is helpful. However, it omits behavioral aspects like pagination, date range limits, data source, or empty-result behavior. Transparency is partial.

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 concise and clearly segmented into Args and Returns. The PRO requirement is front-loaded, and every sentence carries useful information. It is compact without being under-specified.

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?

An output schema exists, so the return field list is a bonus. However, the description does not clarify whether a symbol is mandatory or how many of the date parameters are truly needed. It also fails to relate this tool to its sibling technical_factors_pro. These gaps make it incomplete for an agent to invoke correctly.

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 input schema already describes all four parameters with 100% coverage. The Args section repeats the same descriptions without adding new semantics. The only extra note—trade_date exclusivity—is also present in the schema. Therefore, the description adds little beyond the schema.

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 opens with '技术面因子(行情数据)' which is more a category label than a clear function statement. It lacks an explicit verb like 'retrieve' or 'get', and does not distinguish itself from the sibling tool technical_factors_pro. However, the Returns section clarifies that it provides technical indicators for a security.

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 provides concrete usage constraints: the PRO plan requirement and the exclusivity between trade_date and start/end dates. Yet it gives no guidance on when to prefer this tool over technical_factors_pro, daily, or indicators, and does not clarify whether a symbol is required. Usage context is only partially addressed.

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