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jamesdingAI

stockreport-mcp

by jamesdingAI

get_stock_basic_info

Retrieve fundamental data for Chinese A-share stocks, including company details, industry classification, and listing information, using Baostock-formatted stock codes.

Instructions

    Fetches basic information for a given Chinese A-share stock.

    Args:
        code: The stock code in Baostock format (e.g., 'sh.600000', 'sz.000001').
        fields: Optional list to select specific columns from the available basic info
                (e.g., ['code', 'code_name', 'industry', 'listingDate']).
                If None or empty, returns all available basic info columns from Baostock.

    Returns:
        A Markdown formatted string containing the basic stock information table,
        or an error message.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
fieldsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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 the return format (Markdown table or error message) and the default behavior when fields parameter is None/empty. However, it doesn't mention rate limits, authentication requirements, data freshness, or error conditions beyond the generic 'error message' reference.

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 efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence adds value: the opening statement defines scope, parameter descriptions provide essential usage details, and the return statement clarifies output format. No wasted 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?

Given the tool's moderate complexity (2 parameters, no annotations, but with output schema), the description provides good coverage of purpose, parameters, and return format. However, it lacks information about behavioral constraints (rate limits, auth) and doesn't fully explain the relationship with sibling tools, leaving some contextual gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by providing clear semantics for both parameters: code format (Baostock format with examples), fields parameter behavior (optional list, example values, default behavior when None/empty). This adds substantial value beyond the bare schema.

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 the tool fetches basic information for Chinese A-share stocks, specifying both the action ('fetches') and resource ('basic information for a given Chinese A-share stock'). It distinguishes from siblings like get_hk_stock_basic_info and get_us_stock_basic_info by specifying 'Chinese A-share' scope.

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 context through the stock type specification (Chinese A-share) and parameter examples, but doesn't explicitly state when to use this tool versus alternatives like get_stock_analysis or get_stock_industry. No explicit when-not-to-use guidance or prerequisite information is provided.

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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