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gtorreal
by gtorreal

get_market_volume

Retrieve 24-hour and 7-day trading volume for Buda.com markets, showing buy and sell side breakdowns in base currency values.

Instructions

Returns 24h and 7-day transacted volume for a Buda.com market, split by buy (bid) and sell (ask) side. All volume values are floats in the base currency (e.g. BTC for BTC-CLP). Example: 'How much Bitcoin was sold on BTC-CLP in the last 24 hours?'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
market_idYesMarket ID (e.g. 'BTC-CLP', 'ETH-BTC').
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states what data is returned (24h and 7-day volume split by buy/sell side) and clarifies the units (floats in base currency). However, it doesn't mention potential limitations like rate limits, authentication requirements, or whether the data is real-time or delayed, which would be helpful for a financial API tool.

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 efficiently structured with two sentences: the first states exactly what the tool does, and the second provides a concrete example. Every word serves a purpose, and the most important information (what the tool returns) is front-loaded. No unnecessary information is included.

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?

For a single-parameter read-only tool with no output schema, the description provides good context about what data is returned and in what format. It could be more complete by explicitly stating this is a read-only operation (though implied by 'Returns') and providing more detail about the response structure, but given the tool's relative simplicity, the description is reasonably complete.

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?

The input schema has 100% description coverage, so the schema already fully documents the single parameter. The description doesn't add any additional parameter information beyond what's in the schema, but with only one well-documented parameter, this is acceptable. The example in the description helps illustrate how the market_id parameter would be used in practice.

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 specific action ('Returns'), resource ('24h and 7-day transacted volume for a Buda.com market'), and scope ('split by buy (bid) and sell (ask) side'). It distinguishes itself from sibling tools like get_market_summary or get_ticker by focusing specifically on volume metrics rather than price, sentiment, or other 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 Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an example use case ('How much Bitcoin was sold on BTC-CLP in the last 24 hours?'), which implies this tool is for querying transaction volume. However, it doesn't explicitly state when to use this tool versus alternatives like get_market_summary (which might include volume) or get_trades (which provides individual trades rather than aggregated volume).

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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