Skip to main content
Glama

A股数据 API (A-Share Data API)

ashare_bigorder_rank

L2 全市场主力净额榜(约 5568 只):一次拿到全市场的主力买卖与净额,8 种排序、可翻页、可回看历史。sort 取值:net_in 主力净流入(默认)· net_out 主力净流出 · buy 主力买入额 · sell 主力卖出额 · gain 涨幅 · loss 跌幅 · turnover 换手率 · mcap 市值。行字段(金额单位元):code / name / price / change_pct / main_buy / main_sell(负数) / main_net / turnover_rate / amount / market_cap / concept。用户问'今天主力在买什么/资金流入最多的是哪几只/谁在被砸/哪些板块主力在买'用这个。⭐ 恒等式可自检:main_buy + main_sell == main_net(全市场 100% 成立)。⭐ 下钻路径:本工具选股 → ashare_bigorder(分钟净额)/ ashare_bigorder_split(四分解)看个股结构。⚠️ limit 最大 6000(可一次取全市场,约 1 MB);翻页用 offset。⚠️ market_cap 为数据源原始市值字段,仅供排序/粗筛,⛔ 不要与其它工具的市值字段混用。⚠️ 机构版专属。

Input Schema

NameRequiredDescriptionDefault
dateNo交易日 YYYY-MM-DD(留空=当日)
sortNo排序:net_in/net_out/buy/sell/gain/loss/turnover/mcap(默认 net_in)net_in
limitNo返回条数(默认 100,最大 6000 = 全市场)
offsetNo偏移(翻页用,默认 0)

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden and does disclose useful behavior: approximate universe size (~5568), data volume (~1 MB at limit 6000), amount units in yuan, negative main_sell values, the main_buy + main_sell == main_net identity, market_cap caveat, and institution-only entitlement. It still does not cover authentication mechanics or rate limits in detail, so 4 rather than 5.

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 purpose is front-loaded and most details earn their place: sort modes, use cases, identity check, drill-down path, limits, and caveats. It is still dense and partly repeats schema/output information, especially the sort list and row-field list, so it is not maximally concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity, the existing output schema, and the absence of annotations, the description is complete enough for correct invocation: it covers scope, sort behavior, pagination, output units, self-check identity, drill-down alternatives, and important field caveats. An agent has what it needs to call this tool and interpret the result.

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 repeats the sort values and limit maximum already present in the schema, and only adds minor context such as ~1 MB size and pagination behavior, so it does not substantially exceed the schema's parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: L2 all-market main-force net ranking covering about 5568 stocks, with eight sort modes and pagination. An agent can immediately tell this is a broad ranking/list tool rather than a single-stock detail tool.

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 concrete user questions that select this tool (what main funds are buying, largest inflows, who is being sold, which sectors are being bought) and routes deeper inspection to ashare_bigorder and ashare_bigorder_split. It does not explicitly distinguish when to prefer this over related siblings such as ashare_bigorder_flow or ashare_bigorder_history, so it stops short of full when/when-not guidance.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources