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AlgoVaultLabs

crypto-quant-signal-mcp

get_trade_call

Read-only

Get a BUY, SELL, or HOLD trade call for a single crypto or tokenized-stock perpetual futures, with confidence score and market regime. Combines live exchange data into a clear composite verdict.

Instructions

Returns a composite verdict — BUY SELL HOLD trade call with confidence and market regime — for one crypto or tokenized-stock perpetual futures. One asset only; for a whole-market scan use scan_trade_calls, for US stocks use get_equity_call. Read-only: reads live exchange APIs, no orders. Verified track record, on-chain verified merkle anchor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coinYesBase asset, e.g. BTC ETH SOL signal, or a US stock/ETF ticker (no USDT).
exchangeNoCrypto venue (default Binance), e.g. Binance Bybit OKX Bitget Hyperliquid.
timeframeNoCandle timeframe, 1m to 1d. Default 15m. Crypto quant intraday horizon.
assetClassNoForce engine: 'perp' or 'equity'. Cross-venue multi-exchange AI trading signal.
includeReasoningNoInclude reasoning: trend ranging crypto signal and market regime drivers.
Behavior4/5

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

Annotations declare readOnlyHint=true and destructiveHint=false; the description reinforces with 'Read-only: reads live exchange APIs, no orders,' adding specifics about external data source. 'On-chain verified merkle anchor' adds unique trust context. No contradiction.

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 compact, front-loading the core purpose in the first phrase, and packs relevant scope, alternatives, safety, and verification into two sentences. No redundant wording.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description adequately describes the return value (verdict, confidence, market regime). It covers scope, exclusions, alternatives, and behavioral safety. Given tool complexity, this is sufficient for an agent to select and invoke correctly.

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?

All 5 parameters have descriptive schema coverage, so baseline 3 applies. The description does not add parameter-specific details beyond schema, though 'One asset only' clarifies coin cardinality. The mention of 'tokenized-stock perpetual futures' aligns with assetClass but doesn't add new information.

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?

Clearly states it returns a composite verdict (BUY SELL HOLD) with confidence and market regime for one crypto or tokenized-stock perpetual futures. Explicitly differentiates from siblings: 'for a whole-market scan use scan_trade_calls, for US stocks use get_equity_call.' Strong verb and resource.

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?

Explicitly states 'One asset only' and names alternatives for different scopes, providing clear when-to-use and when-not-to-use guidance. Also mentions read-only nature for implementation context. Distinguishes from get_trade_signal indirectly by mentioning composite verdict.

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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