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bkuri
by bkuri

trading_live_equity

Retrieve real-time profit and loss data for trading sessions to monitor performance and analyze equity curves during live algorithmic trading operations.

Instructions

Get real-time equity curve (P&L) for a session.

Args: session_id: Session ID from_ms: Start time in milliseconds (optional) to_ms: End time in milliseconds (optional)

Returns: Dict with equity curve data points

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYes
from_msNo
to_msNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full disclosure burden. It adequately describes the return value ('Dict with equity curve data points'), but fails to disclose safety characteristics (read-only vs. destructive), error conditions (invalid session_id), rate limits, or whether 'real-time' implies streaming vs. polling behavior.

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 uses a standard docstring format (Args/Returns) that efficiently organizes information. The opening sentence states the purpose immediately, followed by structured parameter and return value documentation. There is no redundant or wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the description adequately covers the three parameters and mentions the return type (sufficient given the output schema exists), it lacks critical contextual details for a financial trading tool: no safety hints, no error handling guidance, and no distinction between paper and live trading sessions despite the complex sibling tool landscape.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Given 0% schema description coverage, the description fully compensates by documenting all three parameters in the Args section: 'session_id' is identified as the session identifier, and the time range parameters are explained with units ('milliseconds') and optionality. This provides essential semantic context missing from the raw schema.

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?

The description opens with a clear verb ('Get') and specific resource ('real-time equity curve (P&L)'), clarifying the scope ('for a session'). The term 'real-time' helps distinguish from historical analysis tools, though it could explicitly clarify whether this applies to both paper and real-money sessions given the sibling tool naming.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'trading_paper_equity_history' or backtesting analysis tools. It omits prerequisites (e.g., requiring an active session) and fails to indicate whether this is for monitoring active trades or post-session analysis.

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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