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find_arbitrage_pairs

Identify arbitrage opportunities by analyzing funding rate magnitude, trading volume, and funding rate direction consistency.

Instructions

Find arbitrage pairs based on funding rate, volume, and rate direction stability.

Args: min_funding_rate: Minimum absolute funding rate to qualify. min_avg_volume: Minimum 24hr volume in USDT. history_limit: Number of historical funding rate records to analyze. stability_threshold: Minimum proportion of funding rates in same direction.

Returns: List of qualifying arbitrage opportunities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
min_funding_rateNo
min_avg_volumeNo
history_limitNo
stability_thresholdNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations provided, and the description does not disclose behavioral traits like whether the operation is read-only, expensive, or requires specific permissions. It describes the criteria but not the underlying behavior or side effects.

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?

Description is concise and well-structured: one-line purpose followed by bulleted parameter descriptions. Every sentence is informative with no redundancy.

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?

The tool has 4 parameters with defaults and an output schema. The description explains what the tool does and the meaning of each parameter. It does not detail the output structure (but output schema exists) or edge cases, but is adequate for its complexity.

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

Parameters4/5

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

Input schema has 0% description coverage, but the description adds meaningful explanations for all 4 parameters: min_funding_rate, min_avg_volume, history_limit, stability_threshold. This compensates for the schema gap, though descriptions are brief.

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?

Description clearly states the tool's action: 'Find arbitrage pairs' based on specific criteria (funding rate, volume, stability). It distinguishes from sibling tools like 'execute_hedge_arbitrage_strategy' (which executes) and other data retrieval tools.

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?

No explicit guidance on when to use this tool versus alternatives. While it lists parameters, it does not provide context for when this tool is appropriate, such as comparing to search-based or direct data retrieval tools among the many siblings.

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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