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MaoBui2907

VNStock MCP Server

by MaoBui2907

get_quote_price_depth

Access detailed price depth quotes for any stock symbol, with output options for JSON, DataFrame, or AI-friendly toon format.

Instructions

Get quote price depth from stock market Args: symbol: str (symbol to get price depth) 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
Behavior3/5

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

No annotations exist, so description partially covers behavior: it mentions return type (DataFrame) and output format options. However, it does not explain what 'price depth' entails (e.g., bid/ask levels) or side effects (none obvious).

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 structured with Args and Returns sections, making it easy to parse. It is reasonably concise, though the Returns line is somewhat redundant given the schema defaults.

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 purpose and parameters but lacks details about the returned data structure (e.g., columns of the DataFrame). For a data-retrieval tool, this omission reduces 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?

With 0% schema coverage, the description fully explains both parameters: symbol and output_format, including the default and meaning of 'toon'. This adds essential 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 clearly states the tool gets quote price depth, which is a specific market data type. It distinguishes from siblings like get_quote_history_price or get_quote_intraday_price by using the term 'price depth'.

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 (e.g., get_quote_price_with_indicators). No prerequisites or context 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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