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mDemarco12

bull-milker-mcp

by mDemarco12

get_quarterly_transaction_summary_tool

Compile filled trades into quarterly summaries showing trade count, buy/sell split, gross notional, and symbols traded. Specify start and end dates; read-only for paper trading.

Instructions

Compiles filled trades into quarterly buckets labeled Q126, Q226, Q326, Q426, etc. (Q<2-digit year>). Each quarter includes trade count, buy/sell split, gross notional traded, and symbols traded. No cost-basis matching — for realized gains/losses use get_quarterly_tax_summary instead.

start/end are 'YYYY-MM-DD' strings. If start is omitted, moomoo's default lookback (~90 days) applies and older quarters will be incomplete — the response includes a '_lookback_warning' field in that case. Read-only, works on paper trading (defaults to SIMULATE).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
startNo
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses read-only nature, paper trading default (SIMULATE), and the _lookback_warning field when start is omitted. It does not fully specify the return structure (e.g., exact fields or error handling), but adds substantial behavioral context beyond the schema.

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?

The description is two short paragraphs with no fluff. The first sentence states the core purpose, the second handles alternatives, and the third covers parameters and warnings. Every sentence earns its place, and it is front-loaded with the most important information.

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 tool with 2 optional parameters and no output schema, this description covers purpose, usage, parameter semantics, operational context (read-only, paper trading), and a returning warning field. It could mention the exact response format (e.g., a list of quarter objects) but the content is sufficiently complete for an AI agent to select and invoke the tool correctly.

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 must compensate. It explains start/end are 'YYYY-MM-DD' strings and details the consequence of omitting start (default lookback and warning). It doesn't explicitly explain what happens if end is omitted, but the provided format and behavior for start add significant meaning beyond the bare schema.

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 states the tool compiles filled trades into quarterly buckets labeled Q126, etc., including trade count, buy/sell split, gross notional, and symbols. It also distinguishes itself from get_quarterly_tax_summary_tool by explicitly noting it does no cost-basis matching, a clear differentiator.

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

Usage Guidelines5/5

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

Explicitly directs users to use get_quarterly_tax_summary_tool for realized gains/losses instead, and explains the behavior when start is omitted (default ~90-day lookback). This provides clear when-to-use and when-not-to-use guidance.

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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