Crypto Data & Market Analysis Agent

get_eth_whale_flows

Read-onlyIdempotent

Large ETH transfers (>100 ETH) to and from live exchange hot wallets (Binance, Coinbase, Bitfinex) in the last 2 hours. Inflows to exchanges suggest potential selling pressure, outflows suggest accumulation. Call for smart-money signals and exchange flows. Wallets that could not be read are listed under "unavailable" rather than dropped, so an empty result is never mistaken for a quiet market. The response also states how far back each wallet could actually be read: the busiest exchange wallets produce thousands of transfers an hour, and a tool that silently sees only the last few minutes of one reports calm that was never measured.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description
`flows`	Yes	Large ETH transfers to and from known exchange wallets, largest first.
`coverage`	Yes	How much of that window each wallet could actually be read back over. A busy wallet can exhaust one page before reaching the far end.
`unavailable`	Yes	Exchange wallets that could not be read. An empty flows list with entries here means nothing was read, not that nothing moved.
`windowMinutes`	Yes	The window asked for, in minutes.

TDQS

A4.7/5.0

Behavior5/5

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

The description discloses that 'wallets that could not be read are listed under "unavailable" rather than dropped' and that the response states 'how far back each wallet could actually be read.' These are critical behavioral details beyond the readOnlyHint annotation, preventing misinterpretation of empty results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is longer than the minimal two-sentence version, but every sentence adds value: interpretation of inflows/outflows and data-completeness caveats. It is front-loaded with the core purpose, and the extra sentences are justified given the risk of misreading empty results.

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 a zero-parameter schema and an output schema present, the description covers all necessary context: what data is returned, how to interpret it for smart-money signals, and how completeness is ensured. The description leaves no critical gap for tool selection.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero parameters, so there is no parameter ambiguity. The description effectively defines the implicit query criteria (threshold >100 ETH, exchanges, 2-hour window), which fully compensates for the empty schema.

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 opens with 'Large ETH transfers (>100 ETH) to and from live exchange hot wallets (Binance, Coinbase, Bitfinex) in the last 2 hours,' which precisely names the resource and scope. It also clarifies the intent with 'Call for smart-money signals and exchange flows,' distinguishing it from general market data 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 phrase 'Call for smart-money signals and exchange flows' is explicit when-to-use guidance. However, it does not name alternative tools for different types of flows, so the 'when not to use' aspect is missing.

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

A4.2/5.0

Disambiguation4/5

Most tools target distinct domains (network, market, derivatives, macro, on-chain flows), and overlapping tools like get_derivatives vs get_derivatives_aggregate are clearly differentiated by scope and detail level. However, get_crypto_market and get_market_dominance both cover market-wide data, and get_btc_network and get_eth_whale_flows both touch on-chain activity, which could cause some confusion.

Naming Consistency5/5

All tool names follow a consistent get_ prefix with descriptive nouns (e.g., get_btc_network, get_defi_overview, get_execution_cost). The pattern is uniform across all 16 tools, with no camelCase or inconsistent verb styles, making it very predictable for an agent.

Tool Count5/5

With 16 tools, the server covers a broad but coherent domain of crypto market analysis—prices, on-chain, derivatives, macro, sentiment, and execution. Each tool addresses a distinct analytical need, and the count is well-scoped for a comprehensive agent, not excessive given the breadth of features.

Completeness4/5

The surface is remarkably complete for a market analysis agent, covering spot, derivatives, on-chain, macro, sentiment, history, and execution costs. Minor gaps exist: no direct tool for decentralized exchange (DEX) trading volumes or specific coin list discovery, and no tool for order book depth beyond the execution cost tool. However, agents can work around these with existing tools.

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