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shenqingtech

deepq-financial-toolkit

by shenqingtech

个股股性分析:换手率得分、流通市值得分、涨停得分

stockFlexibility

Analyzes stock flexibility by calculating turnover rate, market cap, and limit-up performance scores for A-share stocks.

Instructions

个股股性分析:换手率得分、流通市值得分、涨停得分

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesA股股票名称或代码

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
msgYes
codeYes
dataNo
Behavior1/5

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. However, it fails to describe any behavioral traits such as whether this is a read-only operation, if it requires specific permissions, potential rate limits, or what the output entails (e.g., scores as numerical values or ratings). The description only lists output components without explaining the tool's behavior.

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

Conciseness2/5

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

The description is extremely concise but under-specified, consisting of a single phrase that mirrors the title. While it avoids verbosity, it fails to provide essential information, making it inefficient in conveying purpose or usage. Conciseness should not come at the cost of clarity, so this scores low due to lack of substantive content.

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 complexity implied by analyzing multiple scores for stocks, the description is incomplete. No annotations are provided to clarify behavior, and while an output schema exists (which might explain return values), the description doesn't adequately cover the tool's purpose, usage, or behavioral aspects. For a tool that likely involves data retrieval or analysis, more context is needed to guide effective use.

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 parameter 'query' clearly documented as 'A股股票名称或代码' (A-share stock name or code). The description adds no additional meaning beyond this, as it doesn't mention parameters at all. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema adequately handles parameter semantics without need for description enhancement.

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 Guidelines1/5

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 any context, prerequisites, or comparisons to sibling tools like stockFunAnalysis or stockTechAnalysis, which might offer overlapping or complementary functionality. This leaves the agent with no basis for selection among similar tools.

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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