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jackdark425

AIGroup Market MCP

by jackdark425

Company Performance Us

company_performance_us

Fetch US stock performance data with income, balance, cash flow statements and financial indicators for any listed company.

Instructions

获取美股上市公司综合表现数据,包括利润表、资产负债表、现金流量表和财务指标数据

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ts_codeYes美股代码,如'NVDA'表示英伟达,'AAPL'表示苹果,'TSLA'表示特斯拉
data_typeYes数据类型:income(利润表)、balance(资产负债表)、cashflow(现金流量表)、indicator(财务指标)
start_dateYes起始日期,格式为YYYYMMDD,如'20230101'
end_dateYes结束日期,格式为YYYYMMDD,如'20231231'
periodNo特定报告期,格式为YYYYMMDD,如'20231231'表示2023年年报。指定此参数时将忽略start_date和end_date
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses that the tool returns performance data including financial statements and indicators, which suggests a read operation. However, it does not detail any behavioral traits such as rate limits, authentication requirements, or response format (no output schema).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose. It is front-loaded with the main function and contains no unnecessary words.

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?

The tool has 5 parameters with full schema descriptions, and the description lists the types of returned data. This is adequate for an agent to understand the tool's capability. However, it does not explain the optional 'period' parameter's effect beyond what the schema provides, but the schema already covers it. The description is complete enough for a data retrieval tool of moderate complexity.

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% as each of the 5 parameters has a description in the schema. The description does not add extra meaning beyond what is in the schema—it merely reiterates the data types. Baseline score of 3 is appropriate.

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 specifies '获取美股上市公司综合表现数据' (get comprehensive performance data of US-listed companies) and lists specific data types (income statement, balance sheet, etc.). This clearly identifies the tool's function and distinguishes it from siblings like 'company_performance' and 'company_performance_hk' through the explicit '美股' (US stocks) reference.

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 implies usage for retrieving US stock performance data, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., when to use 'company_performance_hk' for Hong Kong stocks). No exclusions or when-not scenarios are 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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