Bit2Me MCP Server

pro_get_order_trades

Read-onlyIdempotent

Retrieve all individual trade executions for a specific order, including price, amount, fees, and date. Analyze how large orders were filled across multiple trades.

Instructions

Gets all individual trades (executions) associated with a specific order. Returns detailed execution data including price, amount, fees, and date for each fill. Useful for analyzing how a large order was executed across multiple trades. [PRIVATE]

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "order_id": "<order_id>"
    },
    "name": "pro_get_order_trades"
  }
}

Input Schema

Name	Required	Description	Default
`jwt`	No	Optional session token for authentication. API keys are recommended for most use cases.
`order_id`	Yes	Order UUID to filter or retrieve specific order details

Schema Changelog

Changes observed during successful MCP inspections.

First observedv4.1.4Jun 11, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already cover the basic safety profile (read-only, non-destructive, idempotent), and the description adds beyond that by disclosing the return content: price, amount, fees, and date for each fill. The [PRIVATE] flag also hints at restricted access. It does not cover pagination, but the bar is lower given the strong annotation set.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences plus a privacy marker, with the core function stated first. Each sentence contributes either purpose, expected output, or usage context. There is no redundant phrasing or filler.

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 simple retrieval tool with one required parameter, the description covers what it does, what data it returns, and when it is useful. There is no output schema, so the description's return-field disclosure is valuable. It could mention pagination or behavior for orders with no trades, but those are not essential for correct invocation.

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 coverage is 100%, so the schema already documents both parameters adequately. The description reinforces that order_id selects the specific order whose fills are returned, but it does not add significant new parameter-level meaning. A baseline of 3 is appropriate when the schema carries the descriptive weight.

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?

The description clearly identifies a specific action ('Gets all individual trades') and a specific resource ('associated with a specific order'). It distinguishes this tool from broad trade-listing calls like pro_get_trades by emphasizing order-level execution data. The mention of 'executions' and 'fills' further disambiguates its purpose.

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 provides a clear use case: analyzing how a large order was executed across multiple trades. It also implies this is the order-specific variant among trade-related tools, though it does not explicitly name sibling alternatives or state when not to use it. The context is clear enough for an agent to select it appropriately.

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

Deploy Server