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iuk-ink

Binance MCP Server

强平订单

trading_force_orders
Read-onlyIdempotent

Retrieve Binance futures force liquidation and auto-deleveraging (ADL) order records. Filter by symbol and auto-close type to analyze forced position closures.

Instructions

返回:强平/自动减仓(ADL)订单记录。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
symbolNo
autoCloseTypeNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed5 schema fields changedv3.0.1
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / properties / autoCloseType / description
      Removed value: -"LIQUIDATION=强平 / ADL=自动减仓"
    • removedInput schema / properties / limit / description
      Removed value: -"数据量限制"
    • changedInput schema / properties / limit / maximum
      Previous value: -1000New value: +100
    • removedInput schema / properties / symbol / description
      Removed value: -"交易对符号 如 BTCUSDT"
  2. Addedv2.0.3

TDQS

C2.7/5.0
Behavior3/5

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

The provided annotations readOnlyHint/idempotentHint already cover the safety profile, and the description adds that the returned records are specifically force-liquidation/ADL. However, it discloses no additional behavioral details like pagination limits, what populates the 'ADL' vs 'DIQUIDATION' subtypes, or open-world behavior beyond the annotations.

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 a single, front-loaded sentence that wastes no words and immediately conveys the core return type. It is appropriately compact, though the compactness comes at the expense of the other information an agent needs.

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?

With no output schema, no parameter descriptions, and no usage notes, the description is too thin to be considered complete. An agent cannot know how to safely or usefully set 'limit', 'symbol', or 'autoCloseType' from the description alone, nor what fields the returned record list will contain.

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

Parameters1/5

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

There are 3 parameters, schema description coverage is 0%, and the description does not mention any of them. Plot, autoCloseType, or how filtering works. The schema namesand enum are self-evident to some degree, but the description provides no extra semantic guidance, so it completely fails to compensate for the absence of property descriptions.

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 uses a specific verb ('返回') and a precise resource ('强平/自动减仓(ADL)订单记录'), making the tool's purpose clear. It also inherently distinguishes this from general order-history tools, though it does not explicitly name a sibling.

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?

The description gives no context on when to prefer this over alternatives such as trading_order_history or trading_trades. There is neither an explicit 'when to use' statement nor any comparison with sibling 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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