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onchaincheck

arbitrum_large_trades

Whale and large-trade tracker for an ERC-20 on Arbitrum One: 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 Arbitrum One
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

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does useful work: it discloses that coverage is limited to the token's deepest WETH/USDC Uniswap v3 pools, that launch history is returned only when recorded, and that the call costs $0.02 USDC on Base via x402. It does not describe rate limits, error/empty behavior, or payment mechanics in more detail, preventing a top score.

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 dense but front-loaded and every clause contributes useful scope, output, or cost information. It could be easier to scan if split into shorter sentences, but it avoids filler and repetition.

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 complex, paid, multi-output tool with no output schema and no annotations, the description explains the returned data well: largest trades, volume/net flow, top wallets, and conditional launch history. It is nearly complete, with remaining gaps around error behavior and explicit alternative-tool routing.

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 parameters are already well documented. The description conceptually echoes the time window and USD-size filtering via 'last N minutes' and 'largest trades,' but it adds little parameter-level meaning beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that this is a whale/large-trade tracker for an ERC-20 on Arbitrum One, including buys/sells in the last N minutes on Uniswap v3 WETH/USDC pools plus launch history. It distinguishes itself from other-chain large-trade siblings by naming Arbitrum One, but it does not explicitly contrast itself with nearby siblings like arbitrum_token_snapshot or token_risk_check.

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 implied by the scope: use it for recent large trades and wallet flow on an Arbitrum ERC-20, with optional launch-history context. However, there is no explicit when-to-use/when-not-to-use guidance and no named alternative tools, so the agent must infer routing from the description 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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