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onchaincheck

eth_large_trades

Whale and large-trade tracker for an ERC-20 on Ethereum: every buy and sell in the last N minutes on the token's deepest WETH/USDC pools (Uniswap v3), with USD size, side, wallet and transaction for the largest trades, buy/sell volume and net flow, and the wallets that bought or sold the most; plus the token's launch from our history (first-sight risk score, liquidity after 24 h/7 d/30 d, deployer record) when we recorded it. Costs $0.02 USDC on Base via x402.

Input Schema

NameRequiredDescriptionDefault
limitNoMax trades listed, 1 to 40, default 20
tokenYesToken contract address on Ethereum
minUsdNoOnly list trades at least this large in USD, default 1000
minutesNoLook-back window in minutes; 5 to 240, default 60 (capped at 12,000 blocks, about 50 minutes on Arbitrum)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the data source (deepest WETH/USDC Uniswap v3 pools), the cost and payment rail ($0.02 USDC on Base via x402), and the important coverage caveat that launch history is only present 'when we recorded it'. It stops short of describing rate limits, error/failure modes, or empty-result behavior.

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?

Content is front-loaded with the resource and then the returned data, and every clause (pool selection, caveat, pricing) carries information. It is a long run-on sentence with heavy semicolon/comma stacking, which costs a little readability, but there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and no annotations, the description adequately explains what comes back (trade list, aggregates, top wallets, conditional launch history) and its cost. Minor gaps remain: no statement of what happens when the token lacks qualifying pools or no trades fall in the window, and nothing on response size/latency.

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?

Schema description coverage is 100%, so the schema already documents all four params with ranges and defaults; baseline 3 applies. The description adds only light framing ('last N minutes', 'largest trades', implicitly minUsd as a size floor) and no new syntax or interpretation guidance beyond the 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 names a specific verb+resource ('Whale and large-trade tracker for an ERC-20 on Ethereum') and enumerates the concrete data returned (USD size, side, wallet, tx, volume, net flow, top wallets, launch history). It implicitly distinguishes itself from the siblings arbitrum_large_trades / base_large_trades / polygon_large_trades by the chain qualifier 'on Ethereum'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: an agent can infer it is for large-trade/whale flow on a specific ERC-20, and the minUsd/minutes params reinforce that. But there is no explicit when-to-use or when-not-to-use guidance versus nearby siblings such as eth_token_snapshot, token_risk_check or deployer_record, nor any note on prerequisites (e.g. that the token must have deep WETH/USDC Uniswap v3 pools for meaningful data).

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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