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sv

MCP Paradex Server

by sv

paradex_orderbook

Read-only

Retrieves order book data to analyze market depth and detect order imbalances, helping optimize entry and execution.

Instructions

Analyze market depth and liquidity to optimize order entry and execution.

Use this tool when you need to:
- Assess true liquidity before placing large orders
- Identify potential support/resistance levels from order clusters
- Determine optimal limit order prices for higher fill probability
- Detect order imbalances that might signal price direction

Understanding the orderbook is essential for effective trade execution,
especially for larger orders or in less liquid markets.

Example use cases:
- Finding the optimal limit price to ensure your order gets filled
- Estimating potential slippage for market orders of different sizes
- Identifying large resting orders that might act as support/resistance
- Detecting order book imbalances that could predict short-term price moves

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
market_idYesMarket symbol to get orderbook for.
depthNoThe depth of the orderbook to retrieve.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already indicate readOnlyHint: true. The description adds behavioral context by detailing how the orderbook data supports trade execution decisions, reinforcing the read-only nature without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with an opening sentence and bullet points, but it includes some motivational language ('Understanding the orderbook is essential...') that adds length without critical value. Could be more concise.

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's read-only nature, existing parameter descriptions, and presence of an output schema, the description covers use cases and interpretation comprehensively, making it contextually complete for an agent.

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% for both parameters, and the description does not add significant new details beyond confirming their roles in depth analysis. Baseline of 3 is appropriate.

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 tool analyzes market depth and liquidity to optimize order entry, with specific use cases. However, it does not explicitly differentiate from sibling tools like paradex_bbo, which might also relate to market data.

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 provides a clear bullet list of when to use the tool, including assessing liquidity, identifying support/resistance, and detecting imbalances. It does not explicitly state when not to use it or compare to alternatives, but the context is strong.

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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