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questflowai

Aster Finance MCP Server

by questflowai

depth

Retrieve order book data for cryptocurrency trading pairs to analyze market depth and liquidity for informed trading decisions.

Instructions

Get the order book for a symbol.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of results. Default 500, max 1000.
symbolYesTrading symbol, e.g., BTCUSDT

Implementation Reference

  • src/index.ts:55-66 (registration)
    Registration of the 'depth' tool, including name, description, and input schema in the tools array.
    {
      name: 'depth',
      description: 'Get the order book for a symbol.',
      inputSchema: {
        type: 'object',
        properties: {
          symbol: { type: 'string', description: 'Trading symbol, e.g., BTCUSDT' },
          limit: { type: 'number', description: 'Number of results. Default 500, max 1000.' },
        },
        required: ['symbol'],
      },
    },
  • Input schema for the 'depth' tool defining parameters symbol (required) and optional limit.
    inputSchema: {
      type: 'object',
      properties: {
        symbol: { type: 'string', description: 'Trading symbol, e.g., BTCUSDT' },
        limit: { type: 'number', description: 'Number of results. Default 500, max 1000.' },
      },
      required: ['symbol'],
    },
  • Handler implementation for 'depth' tool, which makes a GET request to Binance Futures API /fapi/v1/depth endpoint with provided arguments.
    case 'depth':
      return makeRequest('GET', '/fapi/v1/depth', args);
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves order book data but omits critical details such as rate limits, authentication requirements, data freshness, or pagination behavior. This is inadequate for a tool that likely involves real-time market data access.

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 a single, direct sentence that efficiently conveys the core functionality without unnecessary words. It is front-loaded with the essential action and resource, making it highly concise and well-structured for quick comprehension.

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

Completeness2/5

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

Given the complexity of financial trading data, lack of annotations, and absence of an output schema, the description is insufficient. It does not explain the return format (e.g., bids/asks arrays), data structure, or any behavioral traits like rate limiting, which are crucial for effective tool use in this domain.

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?

The input schema has 100% description coverage, clearly documenting both parameters ('symbol' and 'limit') with their types and constraints. The description adds no additional semantic context beyond what the schema provides, such as explaining what an order book entails or how 'limit' affects the response, so it meets the baseline for high schema coverage.

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 action ('Get') and resource ('order book for a symbol'), making the purpose specific and understandable. However, it does not distinguish this tool from potential siblings like 'ticker_bookTicker' or 'exchangeInfo', which might also provide market data, leaving room for improvement in sibling differentiation.

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. With siblings like 'ticker_bookTicker' (which might offer bid/ask prices) and 'exchangeInfo' (which could include order book details), there is no indication of context, prerequisites, or exclusions, leaving usage ambiguous.

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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