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jamesdingAI

stockreport-mcp

by jamesdingAI

get_all_stock

Fetch a list of all A-share stocks and indices with their trading status for a specific date. Returns a markdown table showing stock codes, names, and whether they are trading or suspended.

Instructions

    Fetches a list of all stocks (A-shares and indices) and their trading status for a given date.

    Args:
        date: Optional. The date in 'YYYY-MM-DD' format. If None, uses the current date.

    Returns:
        Markdown table listing stock codes, names, and their trading status (1=trading, 0=suspended).
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo

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 the full burden. It discloses the tool's behavior by specifying the scope ('A-shares and indices'), date handling, and return format. However, it lacks details on rate limits, error conditions, or data freshness, which are important for a data-fetching tool.

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 appropriately sized and front-loaded, with a clear purpose statement followed by structured 'Args' and 'Returns' sections. Every sentence adds value without redundancy, making it efficient and easy to parse.

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, no annotations, and an output schema (implied by 'Returns'), the description is mostly complete. It covers purpose, parameters, and return format well, but could improve by adding behavioral context like data sources or limitations, slightly reducing completeness.

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?

The description adds significant meaning beyond the input schema, which has 0% coverage. It explains the 'date' parameter's optional nature, format ('YYYY-MM-DD'), default behavior (current date if None), and purpose, fully compensating for the schema's lack of documentation.

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's purpose with specific verbs ('fetches a list') and resources ('all stocks (A-shares and indices) and their trading status'), and distinguishes it from siblings by focusing on comprehensive stock listing rather than specific data types like historical prices or financial reports.

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 explicit guidance on when to use this tool versus alternatives is provided. While it implies usage for date-specific stock listings, it doesn't mention when to choose this over tools like 'get_stock_basic_info' or 'get_hs300_stocks', nor does it specify prerequisites or exclusions.

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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