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TickDB Market Data

get_order_book

Get order book (market depth) with bid and ask price levels.

    Returns bids/asks as [price, quantity] arrays, best price first; timestamp in ms.
    Depth is market-defined: US 1, HK 10, CN 5, CN futures 1, HK futures 10,
    crypto up to 1000 levels per side. Actual depth may be lower; no limit parameter.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoProduct type for disambiguation: stock, crypto, forex, indices, futures
symbolYesSingle symbol. Supported: US/HK/CN stocks, CN/HK futures and crypto. E.g. 'AAPL.US', '700.HK', '600519.SH', or 'BTCUSDT'

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedInput schema / properties / limit
      Removed value: -{
      -  "anyOf": [
      -    {
      -      "type": "integer"
      -    },
      -    {
      -      "type": "null"
      -    }
      -  ],
      -  "default": null,
      -  "title": "Limit"
      -}
    • addedInput schema / properties / symbol / description
      Added value: +"Single symbol. Supported: US/HK/CN stocks, CN/HK futures and crypto. E.g. 'AAPL.US', '700.HK', '600519.SH', or 'BTCUSDT'"
    • addedInput schema / properties / type / description
      Added value: +"Product type for disambiguation: stock, crypto, forex, indices, futures"
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does a good job: it discloses the return format ([price, quantity] arrays, best price first), timestamp units (ms), market-specific depth limits, that actual depth may be lower, and that no limit parameter exists. It omits auth/rate-limit context, but for a read-only market data call this is solid disclosure.

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?

Front-loaded with the core purpose, then structured into compact lines covering return format and depth constraints. It is efficient, though the depth enumeration is dense and could be slightly tightened.

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?

No output schema or annotations exist, so the description must supply return-format context — and it does, including array shape, ordering, timestamp units, and depth variability. It does not mention data freshness/real-time nature or error semantics, leaving minor gaps for a 2-parameter tool.

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 100%, so the schema already documents both parameters. The description adds marginal value by explaining that depth is market-defined and no limit parameter exists, but it does not elaborate on the optional 'type' parameter beyond what the schema says.

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?

States a specific verb and resource ('Get order book (market depth)') with bid/ask price levels. None of the sibling tools provide order book data, so the purpose is unambiguous without needing to name alternatives.

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 explains what the tool returns but never states when to use it versus nearby siblings like get_recent_trades, get_ticker, or get_kline. No when-to-use or when-not-to-use guidance is provided.

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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