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Get Whale Flow

get_whale_flow
Read-only

Cumulative whale buy/sell imbalance over hours-to-days from the durable trade tape (≥$25k trades persisted continuously, restart-proof). Returns imbalance ratio (-1..+1), BUY/SELL_DOMINANT verdict, and the largest recent prints. Longer horizons than get_whale_trades (1h buffer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coinYesCoin, e.g. "BTC" (top ~10 by OI are taped)
hoursNoLookback window in hours (default 24)
min_notional_usdcNoThreshold for the sample trades list (tape floor: $25k)

TDQS

A4.5/5.0
Behavior4/5

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

Annotations indicate read-only and open-world. The description adds behavioral details: cumulative, restart-proof, durable tape, persistence of ≥$25k trades. No contradictions; it enhances understanding of data source and reliability.

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?

Three sentences, front-loaded with purpose. Every sentence adds value: what it does (imbalance), output description, and comparison to sibling. No wasted words.

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 explicitly states return values (imbalance ratio, verdict, largest recent prints). All 3 parameters are well-documented in schema with defaults and min/max. The description covers data source, persistence, and use case completely.

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?

Schema coverage is 100%, baseline 3. The description adds context by explaining 'durable trade tape (≥$25k trades)' and that min_notional_usdc sets a threshold for the sample trades list, clarifying the parameter's purpose beyond schema descriptions.

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 returns cumulative whale buy/sell imbalance over hours-to-days from durable trade tape, with specific outputs (ratio, verdict, largest prints). It distinguishes from sibling get_whale_trades by noting longer horizons.

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 explicitly compares to get_whale_trades ('Longer horizons than get_whale_trades (1h buffer)'), indicating when this tool is appropriate. It does not list when not to use or other alternatives, but the comparison is sufficient for a sibling-rich context.

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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TDQS

A3.7/5.0
Disambiguation3/5

Many tools are specialized, but several pairs have fuzzy boundaries: e.g., get_funding_rates vs get_top_funding_rates, get_basic_macro vs get_macro_context, get_simple_iv vs get_options_iv. An agent could easily select the wrong one.

Naming Consistency4/5

Most tools follow a 'get_X' pattern with descriptive noun phrases. There are a few exceptions like 'create_api_key' and 'search_markets', but overall the convention is consistent and readable.

Tool Count2/5

With 47 tools, the server is overloaded. While the domain is broad, this many tools makes discovery and selection difficult for an agent, reducing coherence.

Completeness5/5

The tool set covers an impressively wide range: macro data, funding, prediction markets, OI history, whale tracking, risk analytics, position sizing, backtesting, and signal generation. It leaves no obvious gaps for a crypto trading assistant.