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Agent Data API

base_large_trades

Whale and large-trade tracker for an ERC-20 on Base: every buy and sell in the last N minutes on the token's deepest WETH/USDC pools (Uniswap v3 or Aerodrome), 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. Costs $0.02 USDC on Base via x402.

Input Schema

NameRequiredDescriptionDefault
limitNoMax trades listed, 1 to 40, default 20
tokenYesToken contract address on Base
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

A4.1/5.0
Behavior4/5

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

With no annotations, the description does real work: it names the data sources (deepest WETH/USDC pools, Uniswap v3 or Aerodrome), the look-back semantics, and, crucially, the $0.02 USDC x402 payment requirement. It does not state failure behavior (e.g., token with no qualifying pools) or whether payment is taken when no trades exist.

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?

Purpose and scope are front-loaded in the first clause, and the trailing sentence carries the non-obvious cost/payment fact. The main sentence is dense and packed with clauses, but each clause adds information rather than 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?

No output schema and no annotations, yet the description fully enumerates the returned fields (USD size, side, wallet, transaction, buy/sell volume, net flow, top wallets) and the payment model. Residual gaps are error/empty-result handling and the true window cap, the latter muddied by the schema's copy-pasted Arbitrum block note.

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%, so baseline is 3; the description adds real meaning by clarifying that only trades in the token's deepest WETH/USDC pools count and that the listing is composed of 'the largest trades', which explains how minUsd and limit interact with scope. It does not, however, address the window cap ambiguity.

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?

States a specific verb+resource ('Whale and large-trade tracker') scoped to an ERC-20 on Base, and enumerates what the result contains. The chain is embedded in the name and description, so it is trivially distinguishable from the arbitrum/eth/optimism/polygon variants without opening a schema.

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?

Implied usage is clear (inspect whale activity on a Base token over a recent window), but there is no explicit when-not guidance and no named alternative such as base_token_snapshot or base_new_pools. The agent must infer the boundary from sibling names alone.

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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