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hamzafaiz17

TradeZylo MCP Server

by hamzafaiz17

get_drawdown_stats

Calculate peak equity, current and maximum drawdown, and recovery status for trading accounts, optionally filtered by account. Use to monitor risk and stay within limits.

Instructions

Calculate equity peak and drawdown statistics for accounts: peak equity, current drawdown in dollars and percent from peak, all-time max drawdown, and recovery status. Can filter for a specific account.

Example questions:

  • "What is my current drawdown from peak equity on my accounts?"

  • "How much drawdown do I have on my FTMO account?"

  • "What was the maximum drawdown ever recorded on account 01?"

  • "Am I close to max drawdown?"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNoOptional account name or ID to filter drawdown stats for

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the computed outputs and that filtering is optional, which is useful, but says nothing about read-only semantics, whether inactive accounts are included, performance/caching, or whether 'recovery status' is a boolean or a value. Adequate but incomplete for a zero-annotation tool.

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 capability is front-loaded in the first sentence, with the filter note second and examples third. Nothing is wasted, though the four example questions are somewhat space-heavy for a single-parameter read tool.

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 one-param, read-only stats tool with no output schema, the description compensates well by enumerating the exact metrics returned, so an agent knows what to expect. Minor residual gaps (units/timeframe, whether stats span all accounts or just active ones) keep it from 5.

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?

Only one parameter with 100% schema description coverage, so the schema already documents 'account' fully. The description's 'Can filter for a specific account' merely restates the schema and adds no format or naming guidance. Baseline 3 is appropriate.

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?

States a specific verb ('Calculate') and resource ('equity peak and drawdown statistics'), then enumerates the exact metrics returned: peak equity, current drawdown in dollars/percent, all-time max drawdown, recovery status. This is well beyond a tautology. It stops short of distinguishing itself from risk-oriented siblings like get_risk_check or get_risk_limits, which also concern drawdown.

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?

The four example questions give concrete, realistic triggers for invoking the tool, including the account-filtering case. That is clear usage context, but there is no explicit when-not or routing to the overlapping siblings (get_overview_stats, get_risk_check), so it lands at 4 rather than 5.

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