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deepq-financial-toolkit

deepq-financial-toolkit

by shenqingtech
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript

ETF实时行情：获取ETF基金最新规模、费率、跟踪误差等基本信息关键数

etfLatestPrice

Retrieve current ETF data including size, fees, and tracking error for investment analysis and decision-making.

Instructions

ETF实时行情：获取ETF基金最新规模、费率、跟踪误差等基本信息关键数

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": "etfLatestPrice"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesETF基金代码或ETF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 of behavioral disclosure. It mentions '实时行情' (real-time quotes), implying up-to-date data, but doesn't specify data freshness, rate limits, authentication needs, or error handling. For a tool with no annotations, this is a significant gap, as it leaves key operational aspects undefined.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the key action and resource, making it easy to parse. However, it could be slightly more structured by separating usage context or behavioral details, but it remains concise and to the point.

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?

Given the tool's complexity (a read operation with one parameter) and the presence of an output schema (which likely defines return values), the description is minimally adequate. It covers the basic purpose but lacks behavioral details (e.g., real-time implications, error cases) and usage guidelines. With no annotations and incomplete contextual info, it meets the minimum threshold but has clear 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 'query' parameter documented as 'ETF基金代码或ETF基金名称' (ETF fund code or ETF fund name). The description doesn't add any additional meaning beyond this, such as format examples or constraints. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema adequately handles parameter semantics without extra help from the description.

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. It doesn't mention sibling tools such as 'etfBasicInfo' (which might provide similar basic info) or 'etfPerformance' (which could include performance metrics), nor does it specify any context or exclusions for usage. This lack of comparative guidance limits its effectiveness in helping an AI agent choose the right tool.

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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