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validateFGridInput

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Validate futures grid bot parameters and get allowable ranges before creating one. Identifies out-of-range inputs via check_code to prevent errors.

Instructions

Validates the input parameters for creating a futures grid bot and returns the allowable ranges for each parameter (investment, profit, grid count, price bounds, leverage, TP/SL, etc.).

Use this endpoint before calling /v5/fgridbot/create to ensure parameters are within valid bounds. The response includes a check_code that indicates which parameter is out of range if validation fails.

Rate limit: 10 requests per second per UID.

Agent hint: Call this endpoint first to get valid parameter ranges before creating a grid bot. If check_code is non-zero, the specific validation error is indicated by the code value.

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": {
      "symbol": "<symbol>",
      "cell_number": "<cell_number>",
      "min_price": "<min_price>",
      "max_price": "<max_price>",
      "leverage": "<leverage>",
      "grid_type": "<grid_type>",
      "grid_mode": "<grid_mode>"
    },
    "name": "validateFGridInput"
  }
}

Input Schema

Name	Required	Description	Default
`symbol`	Yes
`leverage`	Yes
`grid_mode`	Yes
`grid_type`	Yes
`max_price`	Yes
`min_price`	Yes
`tp_sl_type`	No
`cell_number`	Yes
`entry_price`	No
`init_margin`	No
`move_up_price`	No
`stop_loss_per`	No
`move_down_price`	No
`stop_loss_price`	No
`take_profit_per`	No
`take_profit_price`	No
`trailing_stop_per`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.11Jun 19, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Annotations already indicate readOnlyHint=true and openWorldHint=true, and the description adds useful behavioral details beyond that: it returns allowable ranges, includes a check_code that indicates which parameter is out of range, and specifies a rate limit of 10 requests per second per UID. No contradiction with annotations.

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 well-organized: main purpose first, followed by usage guidance, rate limit, and an agent hint. There is minor redundancy, such as mentioning check_code twice and repeating the 'call before creating' instruction, but no filler or irrelevant content.

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

Completeness4/5

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

Given the tool has no output schema, the description reasonably covers what the agent needs: it returns allowable ranges and a check_code for validation failures. It does not describe the exact response shape or the full mapping of check_code values, but the core usage context is complete enough for an agent to invoke it correctly.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It provides category-level mapping (investment, profit, grid count, price bounds, leverage, TP/SL) but does not define each parameter individually. Several parameters like grid_type, grid_mode, entry_price, move_up_price, and trailing_stop_per are only represented by their names and enums, leaving their exact semantics largely to inference.

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 clearly states the tool validates input parameters for creating a futures grid bot and returns allowable ranges. It also differentiates this from creation tools like createFGridBot by positioning itself as the pre-creation validation step. The reference to check_code adds further specificity about what the tool does.

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 explicitly instructs the agent to call this endpoint before creating a futures grid bot, and says to use it first to get valid parameter ranges. It does not explicitly state when not to use it or list alternatives, but the workflow guidance is clear and actionable.

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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