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gtorreal
by gtorreal

get_real_quotation

Obtain accurate price quotations for buying or selling cryptocurrencies on Buda.com. Calculate fill estimates including fees based on live market data without placing orders.

Instructions

Gets a server-side price quotation for a buy or sell on Buda.com. Calls the Buda quotation API to compute an accurate fill estimate including fees, based on live order book state. Prefer this over simulate_order for accurate fee-tier-aware quotes. This is a POST (not idempotent) but does not place an order. Public endpoint — no API key required. Parameters: market_id, type ('Bid'|'Ask'), amount, optional limit price. Example: 'Get an accurate quote to sell 0.05 BTC on BTC-CLP.'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
market_idYesMarket ID (e.g. 'BTC-CLP', 'ETH-BTC').
typeYes'Bid' to buy base currency, 'Ask' to sell base currency.
amountYesOrder size (positive number).
limitNoOptional limit price in quote currency.
Behavior4/5

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

With no annotations provided, the description carries the full burden and discloses key behavioral traits: it's a POST (non-idempotent) but read-only ('does not place an order'), public ('no API key required'), and based on live order book state. It doesn't mention rate limits or error handling, but covers essential operational context.

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 appropriately sized and front-loaded, with each sentence adding value: purpose, technical details, usage guidance, and an example. There's no wasted text, and it's structured for quick comprehension.

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 complexity (financial quotation tool with no annotations or output schema), the description is mostly complete, covering purpose, usage, behavioral traits, and parameters. It lacks details on response format or error cases, but provides enough context for effective use.

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 all parameters thoroughly. The description adds minimal value by listing parameters and providing an example, but doesn't explain semantics beyond what the schema provides, aligning with the baseline for high coverage.

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 tool's purpose with specific verbs ('Gets a server-side price quotation') and resources ('for a buy or sell on Buda.com'), distinguishing it from siblings like 'simulate_order' by emphasizing accuracy and fee-tier awareness.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

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

It explicitly provides when to use this tool ('Prefer this over simulate_order for accurate fee-tier-aware quotes') and when not to use it ('does not place an order'), with clear alternatives named.

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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