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Wudao A-Share Stock Data MCP

by io.github.jcdreamjc
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limit_event_summary

Read-onlyIdempotent

聚合封板/炸板事件流，提炼首封最早、炸板最多、回封最多、尾盘事件和分时情绪拐点 何时使用: 盘中分歧/炸板潮/尾盘事件/反复回封等过程分析；普通复盘不需要。 【链接】rows/items/嵌套股票对象含 code/name；列股必须用 [name(code)](https://stock.quicktiny.cn/quote/<code>) markdown 链接。

Input Schema

NameRequiredDescriptionDefault
topNNo各榜单返回数量，默认 10，最大 50。
typeNo事件类型，当前仅支持 limit_up 涨停封板/炸板事件。跌停池请使用 limit_down 工具。limit_up
formatNocontent[0].text：默认1行 headline；markdown=完整 markdown 表格；json=完整 JSON。
coreOnlyNo是否只保留多次封/炸或封单额较高的核心事件股票，默认 false。
tailStartNo尾盘事件起始时间，默认 14:30:00。
detailLevelNo档位：默认 standard（Agent 可计算标准字段）；summary=压缩摘要；raw=全字段+原始数据。
bucketMinutesNo分时统计桶宽，默认 30 分钟，范围 5-120。
maxRowsPerLevelNo梯队/榜单每层最多返回行数。不传走档位默认（summary=3，standard=5）。
includeFirstBoardNo是否展开首板明细。不传=false（首板只统计数量）。
includeReasonInfoNo是否返回长文本涨停原因 reasonInfo。不传=false。

Output Schema

NameRequiredDescriptionDefault
dataNo
metaNo
successNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / detailLevel / description
      Previous value: -"输出详细度（不传=standard，返回 Agent 可计算标准字段）。summary=压缩摘要；raw=全字段+原始数据。"New value: +"档位：默认 standard（Agent 可计算标准字段）；summary=压缩摘要；raw=全字段+原始数据。"
    • changedInput schema / properties / format / description
      Previous value: -"content[0].text 形态。通常不传=1 行 headline；auction_market_scan / auction_theme_strength 在 standard/raw 档默认直接返回 JSON 明细。markdown=完整 markdown 表格；json=完整 JSON。"New value: +"content[0].text：默认1行 headline；markdown=完整 markdown 表格；json=完整 JSON。"
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "data": {},
+    "meta": {},
+    "success": {}
+  },
+  "type": "object"
+}
  3. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare the safe, read-only, idempotent profile, so the bar is low. The description adds useful non-structured context: the returned data is nested stock objects carrying code/name, and any listed stock must be rendered as a markdown link — a mandatory output requirement an agent would not otherwise know.

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 text is dense but front-loaded: purpose first, then usage, then the linking/format rule. There is no wasted filler. The only minor cost is that the output-format rule is bundled into the same block as usage guidance, slightly blurring structure.

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 10-parameter tool with an output schema and safety annotations already in place, the description covers purpose, routing, and the non-obvious output-format obligation. The absence of explicit sibling differentiation and any return-shape summary beyond the link rule are the only remaining 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?

Schema description coverage is 100% across all 10 parameters, so each parameter's meaning (topN, bucketMinutes, detailLevel, coreOnly, etc.) is already documented in the schema. The description adds little parameter-level semantics beyond noting the nested output shape, so the baseline of 3 applies.

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+resource — aggregating the limit-up/break event stream and extracting named signals (最早首封、最多炸板、最多回封、尾盘事件、分时情绪拐点). This is far more precise than a tautology. However, it never explicitly contrasts itself with close siblings such as limit_events or board_break_analysis, leaving that discrimination to the agent.

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?

It gives an explicit when-to-use list (盘中分歧/炸板潮/尾盘事件/反复回封等过程分析) and an explicit when-not (普通复盘不需要), which is strong routing guidance. It stops short of naming a concrete alternative tool for the excluded case, so it is clear context rather than full when/when-not/alternatives.

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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