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kevynf

AKBridge MCP Server

by kevynf

stock_lhb_stock_detail_em

Read-onlyIdempotent

Fetch an individual stock's Eastmoney Dragon-Tiger ranking detail for a chosen date and buy or sell side. Use it to analyze the top buyer and seller seats and transaction amounts.

Instructions

东方财富网-数据中心-龙虎榜单-个股龙虎榜详情 https://data.eastmoney.com/stock/lhb/600077.html :param symbol: 股票代码 :type symbol: str :param date: 查询日期;需要通过 ak.stock_lhb_stock_detail_date_em(symbol="600077") 接口获取相应股票的有龙虎榜详情数据的日期 :type date: str :param flag: choice of {"买入", "卖出"} :type flag: str :return: 个股龙虎榜详情 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo20220315
flagNo卖出
symbolNo000788

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, covering the safety profile. The description adds the return type (pandas.DataFrame) and the date-source constraint, but discloses nothing about rate limits, pagination, or empty-result behavior for a mutation-free read tool.

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?

Purpose and URL are front-loaded and the param docs are tight, but the :type: lines restate information already carried by the schema and add boilerplate. Adequate, not wasteful, but not every line earns its place.

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?

For a 3-parameter read-only retrieval with no output schema, the description covers purpose, all parameters, the return type, and the cross-tool date dependency. What remains (output columns, pagination) is minor given the tool's scope.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden and does so well: symbol=股票代码, date=查询日期 plus how to obtain it, and flag with its choice set {"买入","卖出"}. The schema has no enum for flag, so the description uniquely supplies those valid values; only the schema defaults go unexplained.

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?

States a specific resource (东方财富 龙虎榜单-个股龙虎榜详情) with a concrete URL example, so the agent knows this retrieves individual-stock dragon-tiger board detail rather than the daily list. It does not explicitly name or distinguish itself from close siblings like stock_lhb_detail_em or stock_lhb_stock_statistic_em, which keeps it at 4.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a concrete prerequisite: the date must be fetched via stock_lhb_stock_detail_date_em(symbol=...), which tells the agent how to sequence calls correctly. It stops short of stating when-not to use this tool or how it differs from the other lhb tools, so no 5.

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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