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bkuri
by bkuri

trading_paper_metrics

Retrieve performance metrics for paper trading sessions to analyze strategy effectiveness with key indicators like total return, Sharpe ratio, and win rate.

Instructions

Get calculated performance metrics for a paper trading session.

Args: session_id: Session ID

Returns: Dict with metrics: total_return, sharpe_ratio, max_drawdown, win_rate, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYes

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 burden of behavioral disclosure. It partially compensates by listing specific returned metrics (total_return, sharpe_ratio, max_drawdown, win_rate), but fails to disclose operational traits such as whether the operation is read-only, computationally expensive, or requires specific session states.

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 description uses a structured docstring format (Args/Returns) that efficiently organizes information. The first sentence front-loads the purpose, and there is minimal redundancy or unnecessary verbosity despite the structured sections.

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?

For a single-parameter tool with an existing output schema, the description adequately covers the basic contract by listing representative metrics. However, it lacks completeness regarding error conditions (e.g., invalid session_id) and behavioral constraints (e.g., session lifecycle requirements).

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

Parameters2/5

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

With 0% schema description coverage, the description must fully compensate for the lack of parameter documentation. It provides only the tautological label 'Session ID' for session_id, without clarifying the expected format, how to obtain it (e.g., from trading_paper_start), or that it specifically refers to a paper trading session ID.

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 clearly states the tool 'Get[s] calculated performance metrics for a paper trading session,' specifying the verb, resource, and domain. It distinguishes itself from sibling tools like trading_paper_trades or trading_paper_equity_history by emphasizing 'calculated performance metrics' (aggregated statistics) rather than raw trade lists or equity curves.

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 trading_paper_status, nor does it specify prerequisites such as whether the session must be active or completed. No workflow context is provided.

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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