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Glama

TradFi perpetuals: stock, index and commodity perps on Binance

get_tradfi_board
Read-only

Retrieve Binance TradFi perpetual board details: mark/index price, basis, funding, open interest, liquidations, venues, and session state. Filter by market or symbol.

Instructions

Call this when the user asks about stock perpetuals (TSLA, NVDA, AAPL, gold, S&P 500...), tokenized-equity perps, TradFi perp funding rates, open interest, liquidations, which exchanges list a stock perp, or whether the equity session is open. Returns Binance's TradFi perpetual board: per contract mark, index, basis, funding, 24h change and volume, open interest, 24h recorded liquidations, other venues listing the same underlying, and the trading-session state per market. Filter by market (EQUITY, HK_EQUITY, KR_EQUITY, CN_EQUITY, COMMODITY, INDEX, PREMARKET) or one symbol.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketNoMarket filter: EQUITY | HK_EQUITY | KR_EQUITY | CN_EQUITY | COMMODITY | INDEX | PREMARKET
symbolNoOne Binance TradFi symbol, e.g. TSLAUSDT

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.27.2

TDQS

A4.3/5.0
Behavior4/5

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

Since annotations already mark it read-only, the description can safely focus on what the tool returns; it does so generously by listing mark, index, basis, funding, 24h volume, open interest, liquidations, other venues, and session state. It also explains the optional filtering behavior by market or symbol, adding context beyond the annotations alone.

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 three sentences and each sentence has a distinct job: trigger conditions, returned fields, and filtering. It is front-loaded with the 'Call this when' list and contains no redundant or decorative 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?

There is no output schema, but the description enumerates the return payload in enough detail for an agent to know what the call provides. With zero required parameters and clear optional filters, an agent can invoke the tool correctly without further guessing.

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?

The input schema already documents both optional params at 100% coverage, so the baseline is 3. The description adds a concrete example symbol (TSLAUSDT) and clarifies that filtering is by market category or by a single symbol, but otherwise reuses the schema's enums and patterns.

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 specifies a concrete verb and resource: 'Returns Binance's TradFi perpetual board' with detailed per-contract metrics. It also enumerates unique application domains (stock perps like TSLA/NVDA/gold, tokenized-equity perps, TradFi funding/OI/liquidations, cross-exchange listings, session state) that clearly set it apart from the crypto-focused siblings.

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 opens with a direct trigger: 'Call this when the user asks about...' followed by several distinct query categories. It does not mention when not to use it or name alternative tools, but the positive conditions are specific enough for an agent to route correctly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.