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Glama

indicators

财务指标(财务数据) 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 period: 报告期 YYYYMMDD(如 20251231 = 2025 年报) ann_date: 公告日期 YYYYMMDD

Returns: JSON 数组;字段: symbol, ann_date, end_date, eps, dt_eps, total_revenue_ps, revenue_ps, bps, ocfps, roe, roe_waa, roe_dt, roa, gross_margin, netprofit_margin, grossprofit_margin, debt_to_assets, current_ratio, quick_ratio, cash_ratio, assets_turn, inv_turn, ar_turn, roic, basic_eps_yoy, dt_eps_yoy, netprofit_yoy, dt_netprofit_yoy, rd_exp

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNo报告期 YYYYMMDD(如 20251231 = 2025 年报)
symbolNo证券代码(带后缀),如 000001.SZ
ann_dateNo公告日期 YYYYMMDD
end_dateNo结束日期 YYYYMMDD
start_dateNo起始日期 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 carries the burden of behavioral disclosure. It does disclose the PRO plan requirement and the 403 response for lower tiers, which is important. It also lists all return fields, giving a clear picture of output. However, it omits other behavioral traits like rate limits, ordering, or error handling beyond 403.

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, with a short header, a single requirement line, and structured Args/Returns lists. It front-loads the key access constraint (PRO) early. The duplication of schema descriptions is somewhat redundant but does not bloat the overall text.

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 covers the PRO requirement, all parameters, and output fields, which is substantial. However, it does not explain how start_date/end_date relate to period/ann_date, leaving ambiguity for a tool with 5 optional parameters. The absence of an actual output schema is partially mitigated by the field list, but some usage semantics remain unclear.

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 description coverage is 100%, and the description's Args section essentially repeats the schema text. No additional meaning is added beyond what the schema already provides. The return field list is useful but not parameter semantics, so the baseline of 3 is appropriate.

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 opens with '财务指标(财务数据)' which clearly states the tool provides financial indicators. The Args and Returns sections further specify it retrieves metrics like EPS, ROE, and margins for a security. It does not explicitly name the action (e.g., 'retrieve'), but the resource is clear and distinct from siblings.

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?

No guidance is given on when to use this tool versus alternatives. The only usage-related note is the PRO requirement and 403 error, which is a constraint rather than a recommendation. Sibling tools like 'fundamentals' or 'technical_factors' are never mentioned.

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