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RedSamerai

a-stock-mcp

by RedSamerai

Dragon Tiger Analyzer

dragon_tiger_analyzer

Retrieve dragon-tiger list entries for a given date, sorted by net buy amount. Filter by reason or minimum net buy to identify active stocks.

Instructions

龙虎榜分析:查询指定日期的上榜个股明细。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo日期,格式 YYYYMMDD,如 "20260907"。不传则默认当天。
top_nNo返回条数上限,默认 30。按净买额降序排列。
reasonNo上榜原因关键词(模糊匹配),如 "跌停"、"涨幅偏离"。
min_net_buyNo最小净买额(元),负值表示允许净卖出。

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

C2.9/5.0
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 only indicates a read-style query and does not mention data source, trading-day availability, result limits, ordering, or any other behavior beyond the schema. There is no contradiction with annotations, but disclosure is minimal.

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 one compact sentence with no filler and the main query scope is front-loaded. It is concise and readable, though it could have included a brief usage note without becoming bloated.

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?

For a read-only query tool with a fully documented parameter schema and an output schema, the description covers the core function. However, it omits domain context that would help an agent distinguish the Dragon-Tiger list from sibling limit-up/down scanners, and it does not mention data source or availability nuances.

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?

Schema description coverage is 100%, so the baseline is 3. The description does not add any meaning beyond the schema for date, top_n, reason, or min_net_buy; all parameter semantics are already present in the structured schema.

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 states a specific verb (查询/query) and resource (指定日期的上榜个股明细, details of stocks that made the Dragon-Tiger list on a date), making the core function clear. It does not explicitly contrast with sibling scanners like scan_limit_up_stocks or scan_limit_down_stocks, so it lacks the differentiation needed for a 5.

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?

There is no guidance about when to use this tool versus the ten sibling analysis tools, nor any mention of prerequisites, exclusions, or alternative tools. The agent must infer appropriate usage entirely from the name and domain context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.