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hamzafaiz17

TradeZylo MCP Server

by hamzafaiz17

get_strategy_stats

Analyze live trading performance by strategy, returning win rate, average PnL, profit factor, and total trades for each setup tag.

Instructions

Cross-reference playbook strategies with actual trade data. For each setup tag/strategy in your trades, returns real win rate, average PnL, profit factor, total trades, and average actual RR in live execution.

Example questions:

  • "Which playbook strategy is performing best in live trading?"

  • "What is the real win rate of my Breakout or ICT strategy?"

  • "Compare live performance across all my strategies"

  • "Show win rate by strategy"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
date_toNoISO date YYYY-MM-DD — analysis end
date_fromNoISO date YYYY-MM-DD — analysis start

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden; it does disclose the returned metrics and implies a read-only aggregation, which is genuinely useful. It does not state permission requirements, whether the analysis respects account scoping, or any pagination/result-size behavior.

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 core purpose and return values are front-loaded in the first two sentences, followed by a scannable example-question list. The examples add retrieval value but make the entry longer than strictly necessary.

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?

With no output schema, the description does the work of explaining return values, which is the key gap it fills for a stats tool. It is adequate overall, though account-scoping and empty-result behavior remain unstated.

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% for both date_from and date_to, so the schema already documents the ISO date format and analysis window. The description adds no additional meaning about the date range beyond what the schema provides, so the baseline of 3 applies.

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 ('Cross-reference playbook strategies with actual trade data') and enumerates exactly what is returned (win rate, average PnL, profit factor, total trades, average actual RR). This clearly separates it from get_playbook (rule definitions) and get_overview_stats (general portfolio stats).

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?

Four example questions give concrete usage triggers ('Which playbook strategy is performing best in live trading?', 'Show win rate by strategy'), making the intended context clear. However, no explicit when-not guidance or named alternatives (e.g., vs. get_overview_stats) are provided.

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