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deepq-financial-toolkit

deepq-financial-toolkit

by shenqingtech
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript

基金业绩：近1年、3年、今年、成立以来的业绩指标，包括：收益率、年化收益率、年化波动、夏普比率、最大回撤、年化超额、信息比率

fundPerformance

Analyze fund performance metrics including returns, volatility, Sharpe ratio, and maximum drawdown for investment evaluation.

Instructions

基金业绩：近1年、3年、今年、成立以来的业绩指标，包括：收益率、年化收益率、年化波动、夏普比率、最大回撤、年化超额、信息比率

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "fundPerformance"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYes基金代码或基金名称

Output Schema

NameRequiredDescriptionDefault
msgYes
codeYes
dataNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.0.0
    • addedInput schema / $schema
      Added value: +"http://json-schema.org/draft-07/schema#"
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observed

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It describes what data is returned but lacks behavioral details such as whether this requires authentication, rate limits, error handling, or how results are formatted (e.g., JSON structure, units). For a data retrieval tool with no annotation coverage, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, dense sentence that lists all metrics and time periods, making it information-rich but somewhat cluttered. It could be more structured (e.g., separating purpose from details) for better readability, though it avoids unnecessary verbosity.

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 complexity (retrieving multiple performance metrics across time periods), the description is reasonably complete in specifying what data is returned. With an output schema present, it doesn't need to detail return values, and the single parameter is well-documented in the schema. However, it lacks usage context and behavioral transparency, which are minor gaps.

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?

The input schema has 100% description coverage, with the single parameter 'query' documented as '基金代码或基金名称' (fund code or fund name). The description adds no additional parameter information beyond what's in the schema, so it meets the baseline of 3 for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tautological: description restates name/title.

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 provides no guidance on when to use this tool versus alternatives. With many sibling tools available (e.g., 'fundBasicInfo', 'etfPerformance', 'fundRecentViews'), there's no indication of context, prerequisites, or comparisons to help an agent choose appropriately.

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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