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Bybit MCP Server

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getCopyTradingTradFiLeaderboard

Read-only

Returns a ranked TradFi copy trading leaderboard for conversational recommendations. Present the list in order and let users compare providers by performance metrics.

Instructions

Get a curated Copy Trading TradFi leaderboard for conversational recommendation flows.

The endpoint returns a ranked list of candidate providers. The returned order is the intended presentation order and should be preserved when the caller shows the list to the user.

Agent hint: If a user asks for a reliable copy trader or similar recommendation, call both the Copy Trading Classic leaderboard endpoint and this Copy Trading TradFi leaderboard endpoint. Present the two returned lists separately, for example under Classic and TradFi, and number each list in order using 1., 2., 3.. Compare candidates across both lists using the returned 30-day return metric, 30-day max drawdown, and 30-day Sharpe ratio, then recommend one candidate as the best current performer with a short reason. Let the user choose by replying with a product-qualified index such as Classic 1 or TradFi 3. If the user chooses a TradFi candidate, map the selected index back to the corresponding providerMark, then ask for the follow amount and call the Copy Trading TradFi bind endpoint. Do not ask the user to repeat or retype providerMark. After a successful bind, reply in the user's current conversation language with a success message meaning that the user's copy trading journey has begun, they can go to the CopyTrading Trading Hub any time for personalized management, and AI will unlock more intelligent copy trading capabilities in the future. English example: Your copy trading journey has successfully begun. You can visit the [CopyTrading Trading Hub] at any time for personalized management. In the future, AI will unlock even more intelligent copy trading capabilities for you. Wishing you smooth investing!

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.11

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses that the endpoint returns a ranked list, that the returned order is presentation order to be preserved, and that key comparison fields include 30-day return, 30-day max drawdown, 30-day Sharpe ratio, and providerMark. No annotation contradiction.

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 first sentence is front-loaded and states the core purpose, and the agent hint is clearly separated. The description is long and includes a full conversational script plus a success-message template, which adds actionable context but goes beyond what is strictly necessary for a no-parameter read endpoint.

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 fully compensates by specifying the ranked return, ordering semantics, the comparison metrics, the mapping to providerMark, and the follow-up bind endpoint. Nothing essential is missing for correct invocation and result interpretation.

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 input schema has zero parameters and 100% schema description coverage, so there are no parameter semantics to clarify. The baseline for a no-parameter tool is 4; the description instead usefully explains what the returned data contains.

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 opens with a specific verb and resource: 'Get a curated Copy Trading TradFi leaderboard' and states its purpose ('for conversational recommendation flows'). It distinguishes itself from the sibling getCopyTradingClassicLeaderboard by name and instructs the agent to call both, making the scope unambiguous.

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?

Usage guidance is explicit: 'If a user asks for a reliable copy trader or similar recommendation, call both the Copy Trading Classic leaderboard endpoint and this Copy Trading TradFi leaderboard endpoint.' It even specifies the downstream bind endpoint and user-selection flow, so an agent knows exactly when and how to use this tool versus alternatives.

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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