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MaoBui2907

VNStock MCP Server

by MaoBui2907

get_company_overview

Get a company overview using its stock symbol. Returns essential data about the company from the Vietnamese stock market.

Instructions

Get company overview from stock market Args: symbol: str output_format: Literal['json', 'dataframe', 'toon'] = 'toon' (output format, 'toon' is optimized for AI) Returns: pd.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes
output_formatNotoon
Behavior1/5

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

The description claims 'Returns: pd.DataFrame', but the input schema includes output_format options of 'json', 'dataframe', and 'toon'. This implies the return type varies, contradicting the description. No annotations are provided, so the description fails to disclose behavioral traits such as idempotency or safety.

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 relatively concise, using a docstring format (Args, Returns). It front-loades the purpose in the first line and only adds necessary details about parameters and return type. Could be slightly more structured by separating description from args.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lacks completeness for a stock market tool. It does not specify what data the overview contains (e.g., price, financials, ratios), nor does it explain how output_format affects the return value. Given the absence of an output schema and many sibling tools, more context is needed.

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?

With 0% schema description coverage, the description attempts to compensate by listing parameters and explaining output_format's meaning ('toon is optimized for AI'). However, the 'symbol' parameter is merely named without elaboration, adding minimal semantic value beyond the schema.

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 states 'Get company overview from stock market' which clearly identifies the action and resource. However, it does not differentiate from numerous sibling tools like get_company_reports or get_company_ratio_summary, lacking specificity on what an 'overview' includes.

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 on when to use this tool versus alternatives. The description only lists arguments and return type, without explaining prerequisites, when to prefer this over other company-related tools, or if there are limitations (e.g., required exchange/symbol format).

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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