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bybit-mcp

bybit-mcp

by JohnnyWic
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

pre_check_order

Check an order's margin, limits, and criteria before placing it to avoid rejection.

Instructions

Pre-check an order before placing it (validates margin, limits, etc.).

Args: category: Product type: inverse, linear, option. symbol: Symbol, e.g., BTCUSDT. side: Buy or Sell. order_type: Market or Limit. qty: Order quantity. price: Order price (required for Limit).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "category": "<category>",
      "symbol": "<symbol>",
      "side": "<side>",
      "order_type": "<order_type>",
      "qty": "<qty>"
    },
    "name": "pre_check_order"
  }
}

Input Schema

NameRequiredDescriptionDefault
categoryYes
symbolYes
sideYes
order_typeYes
qtyYes
priceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description must bear the full load. It states the tool 'validates margin, limits, etc.' but does not disclose whether the operation is read-only, what happens on validation failure (e.g., returns errors, no side effects), or any auth requirements. The behavior is implied but not explicit.

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 is brief (2 lines of purpose + compact Args list). It front-loads the purpose and uses concise parameter descriptions. No redundant information.

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?

No output schema exists, and the description does not explain what the tool returns (e.g., validation passed/failed, error codes). For a pre-check tool, the return behavior is critical. With many sibling tools, additional context on how results inform subsequent actions would improve completeness.

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?

Schema description coverage is 0%, so the description entirely compensates. It lists all 6 parameters with clear explanations: category as product type, price as required for Limit orders. This adds essential meaning beyond the schema's basic types and titles.

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 states 'Pre-check an order before placing it (validates margin, limits, etc.)', which clearly identifies the tool's action (pre-check), resource (order), and purpose (validate constraints). It distinguishes itself from siblings that actually place orders (e.g., place_limit_order, place_market_order).

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

Usage Guidelines4/5

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

The description implies usage context: 'before placing it' suggests a prerequisite step. However, it does not explicitly state when to avoid using the tool (e.g., if order validation is not needed) or mention alternatives among many order-related siblings. The guidance is clear for the intended use case.

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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