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forgequant

CoinGlass MCP Server

by forgequant

CoinGlass Large Orders

coinglass_ob_large_orders
Read-onlyIdempotent

Detect significant limit orders (whale walls) that may act as support/resistance levels in cryptocurrency markets. Filter by exchange or trading pair to identify large orders that could influence price movements.

Instructions

Get large limit orders (whale walls).

Detects significant limit orders that may act as support/resistance. Thresholds: BTC >= $1M, ETH >= $500K, others >= $50K.

Examples: - Current whale walls: action="current" - Historical large orders: action="history"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYescurrent: active large orders | history: historical
exchangeNoFilter by exchange
pairNoFilter by pair
limitNoNumber of orders

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

The description adds valuable behavioral context beyond what annotations provide. While annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, the description adds specific threshold information ('BTC >= $1M, ETH >= $500K, others >= $50K') that defines what constitutes 'large' orders. This quantitative threshold disclosure is important behavioral information not captured in annotations. No contradiction with annotations exists.

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 exceptionally concise and well-structured. It uses only 4 sentences: the first states the core purpose, the second adds threshold context, and the last two provide clear usage examples. Every sentence earns its place with zero wasted words. The information is front-loaded with the most important details first.

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?

Given the tool's moderate complexity, comprehensive annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint), 100% schema coverage, and the presence of an output schema, the description is complete enough. It covers the tool's purpose, quantitative thresholds, and usage examples. With annotations handling safety/behavioral guarantees and the output schema presumably documenting return values, the description focuses appropriately on what's not captured elsewhere.

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?

With 100% schema description coverage, the input schema already documents all 4 parameters thoroughly. The description adds minimal parameter semantics beyond the schema - it only provides examples for the 'action' parameter values. While helpful, this doesn't significantly enhance understanding of parameters like 'exchange', 'pair', or 'limit' beyond what the schema already provides. The baseline of 3 is appropriate given the comprehensive schema 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: 'Get large limit orders (whale walls)' with specific verb ('Get') and resource ('large limit orders'). It distinguishes from siblings by specifying this tool focuses on order book large orders rather than other crypto data like funding rates, liquidations, or market data. The description adds context about detecting support/resistance levels, which further clarifies its unique analytical purpose.

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 provides clear context about when to use this tool through the action parameter examples ('Current whale walls: action="current"' and 'Historical large orders: action="history"'). However, it doesn't explicitly state when NOT to use this tool or mention specific alternatives among the sibling tools (like coinglass_ob_history for general order book history or coinglass_whale_positions for different whale data). The guidance is helpful but lacks explicit exclusion criteria.

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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