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ER-EPR

futu-opend-mcp

by ER-EPR

get_short_data

Fetch short-selling data for HK/US stocks: short volume, short interest, or days to cover. Specify data type for volume or interest.

Instructions

Short-selling data - 每日卖空/卖空量/卖空比例 (volume) or 空头持仓/short interest/ days to cover (interest). HK/US.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numNo
codeYes
data_typeYes
Behavior3/5

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

The description discloses that the tool returns short-selling data with two data types (volume/interest) and market coverage (HK/US). However, no annotations exist, and the description does not mention aspects like data freshness, read-only nature, or rate limits. The name implies read-only, but that is not explicit.

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 very short and to the point, front-loading the core function ('Short-selling data') followed by specifics. It is efficient, though the inclusion of Chinese characters may add noise for some users.

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?

Given the absence of output schema and minimal parameter descriptions, the description should provide more context. It does not explain the meaning of the 'num' parameter or the format of 'code', leaving ambiguity for an AI agent. The market coverage is noted, but essential details are missing.

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

Parameters2/5

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

Schema description coverage is 0%, and the description adds minimal parameter meaning. It explains the enum options (volume/interest) with examples but does not describe the 'code' or 'num' parameters (e.g., what 'num' represents). The description fails to compensate adequately for the lack of schema descriptions.

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 that the tool provides short-selling data (volume or interest) for HK and US markets, which distinguishes it from siblings like get_analyst_consensus, get_capital_flow, etc. The verb 'get' is implied, and the resource is well-specified.

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 is provided on when to use this tool versus alternatives. There is no mention of scenarios where another tool might be more appropriate, nor any exclusion criteria.

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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