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Bybit MCP Server

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getPredictionPortfolioSummary

Read-only

Get a quick aggregate view of your prediction market portfolio, showing total invested, current value, profit/loss, and active and historical position counts.

Instructions

Query an aggregated summary of the authenticated user's prediction market portfolio. Returns total invested amount, current portfolio value, unrealized and realized P&L, and total number of active and historical positions.

AI agent can use this to give users a quick overview of their prediction market performance without listing all individual positions.

Agent hint: Use this for a high-level portfolio overview: total value, total P&L, position counts. For individual position details, use getPredictionPositionList. For historical P&L breakdown, use getPredictionPositionHistory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.1.15

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds meaningful behavioral context beyond the annotations by clarifying that the tool returns an aggregated summary rather than a detailed position list, and by specifying exactly which aggregates are included.

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 is front-loaded with the purpose and return values, followed by use-case guidance and sibling routing. It is slightly redundant because the 'Agent hint' partially restates the earlier overview, but overall it remains compact and useful.

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

Completeness5/5

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

With no parameters and no output schema, the description carries the full burden of explaining the return value, and it does so thoroughly: total invested amount, current portfolio value, unrealized and realized P&L, and active/historical position counts. It also provides the necessary agent routing context, making it complete for this tool's complexity.

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

Parameters4/5

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

The tool has zero parameters and an empty input schema, so there are no parameter semantics for the description to clarify. Per baseline for zero-parameter tools, this is fully adequate.

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?

The description uses a specific verb and resource, 'Query an aggregated summary of the authenticated user's prediction market portfolio', and enumerates the exact returned metrics. It also distinguishes itself from getPredictionPositionList and getPredictionPositionHistory, so an agent can tell this tool apart from its siblings.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool: for a high-level portfolio overview with total value, total P&L, and position counts. It also names the alternatives for individual position details and historical P&L breakdown, giving clear routing guidance.

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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