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michaelfeng

FactorHub MCP Server

by michaelfeng

get_factor_scores

Retrieve detailed scoring metrics for a single A-share factor, including annualized return, Sharpe ratio, max drawdown, volatility, Alpha, Beta, and IC mean.

Instructions

获取单个因子的详细评分指标:年化收益、夏普比率、最大回撤、波动率、Alpha、Beta、IC均值等。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
start_dateNo
end_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. The description lists key output metrics but does not disclose behavior such as date range handling, error conditions, or performance implications. It adds value by detailing output but lacks depth.

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 a single concise sentence that effectively communicates the tool's purpose. It is front-loaded with the key action and resource. While not overly lengthy, it could be slightly more structured (e.g., breaking out parameters).

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?

An output schema exists, so the description need not explain return values in detail, but the tool has 3 parameters and no annotations. The description provides a list of key metrics but omits context like default date range, authentication needs, or data completeness. It is adequate but not comprehensive.

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 coverage is 0%, meaning the description does not explain any parameter. It implies 'code' identifies the factor but gives no details on 'start_date' or 'end_date' (e.g., format, default behavior). The description does not compensate for the schema gap.

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 retrieves detailed scoring indicators for a single factor and lists specific metrics (annualized return, Sharpe ratio, etc.). It distinguishes the tool from siblings like list_factors (which lists all factors) and get_factor_nav (which likely returns net asset value). However, it does not explicitly contrast with siblings.

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?

The description gives no guidance on when to use this tool versus alternatives, nor any prerequisites or restrictions. It lacks exclusions or context like 'only for single factor' which is implicit.

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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