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?

Beyond the readOnly/openWorld/idempotent annotations, the description reveals crucial behavioral details: the threshold for transfers, the interpretation of inflows/outflows, the 'unavailable' wallet handling to avoid false empty results, and the honest disclosure of read-depth limitations. This goes far beyond the annotations.

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 concise yet rich, with every sentence adding value. It is front-loaded with the core function, followed by interpretation guidance, and a critical caveat about data coverage. No word is wasted, and the structure supports quick comprehension.

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?

For a zero-parameter tool, the description covers the data scope, interpretation, edge cases, and measurement limitations. The output schema exists but need not be repeated. It is complete and self-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.

Parameters4/5

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

The tool has zero parameters, so the baseline is 4. The description adds meaningful context about the data returned and its interpretation, but since there are no parameters to explain, this score is appropriate.

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 a specific verb and resource: it reports large ETH transfers (>100 ETH) to and from exchange hot wallets. It distinguishes itself from sibling tools by specifying the ETH exchange flow focus and the 2-hour window, making its unique purpose unmistakable.

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 says 'Call for smart-money signals and exchange flows,' providing a direct usage context. It does not name alternatives or state when not to use, but the clear purpose and context are sufficient for guiding an agent.

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

All Crypto Data & Market Analysis Agent tools Inspect

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TDQS

A4.4/5.0

Disambiguation5/5

Each tool targets a distinct data domain—network health, market prices, news, DeFi, derivatives per-venue vs aggregate, economic calendar, ETH address, whale flows, execution cost, sentiment, implied volatility, macro rates, market brief, dominance, history, and traditional market quotes. The only similar pair (get_derivatives vs get_derivatives_aggregate) is clearly differentiated by level of detail, so there is no real ambiguity.

Naming Consistency5/5

All tools follow the get_<domain> pattern with descriptive noun phrases (e.g., get_btc_network, get_eth_whale_flows, get_market_brief). No mixed verb styles or casing conventions appear, making the naming fully predictable and consistent.

Tool Count4/5

At 17 tools, the surface is slightly above the ideal 3-15 range, but the breadth of the domain—spot, derivatives, on-chain, macro, sentiment, and execution—justifies each tool. It's borderline but each tool earns its place in a comprehensive market analysis agent.

Completeness5/5

The toolset covers nearly every major facet of crypto market analysis: prices, history, dominance, derivatives, on-chain activity, DeFi, macro, economic calendar, sentiment, implied volatility, execution cost, and a composite brief. Minor gaps like historical OHLCV or multi-chain on-chain analytics are not critical given the agent's stated focus.

Resources

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