Use this when the user asks about THEIR MCPify account: balance, withdrawable, open positions with PnL and liquidation prices, and whether agent trading is armed.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safe-read nature is covered. The description adds useful context about what data is returned, but does not disclose additional behavioral traits such as response format, whether data is real-time, or any auth/availability assumptions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is one well-structured sentence that front-loads the usage condition and then lists the concrete data types. There is no filler, repetition, or redundant restatement of the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only account retrieval tool, the description covers the main content areas a user would ask about. It could be more complete by explicitly distinguishing itself from order/trade-history tools, but the sibling names and the specificity of 'open positions' largely cover that gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema coverage is 100%, so there is no parameter information to supplement. The description compensates by explaining what the tool returns, which is the relevant semantic content for a no-input tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly ties the tool to a specific user intent: asking about the user's MCPify account. It enumerates the exact data categories (balance, withdrawable, open positions with PnL/liquidation prices, and whether agent trading is armed), which clearly distinguishes it from account-history siblings like get_my_open_orders and get_my_trade_history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The opening phrase 'Use this when the user asks about THEIR MCPify account' provides a clear trigger condition. It does not explicitly state when not to use it or name alternative tools, but the sibling list and the enumerated account-specific scope make the intended use reasonably unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool maps to a distinct resource/action: market data, account state, resting orders, audit records, fills, order placement, and risk management. The only close pair, preview_order and place_order, is clearly delineated as validation vs execution.
All tool names follow a consistent snake_case verb_noun pattern (get_, place_, cancel_, close_, set_). The object names are uniform and predictable, making the set easy to navigate.
13 tools is well-scoped for a trading server: market data, account/order queries, execution, and position risk each have coverage without redundancy or bloat.
The surface covers the core trading lifecycle: market data, account, preview/place/cancel, close position, TP/SL, and historical records. Minor gaps exist (e.g., no modify-order operation and no standalone position detail endpoint), but agents can work around them via cancel/replace and get_my_account.