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Agent Data API

polygon_large_trades

Whale and large-trade tracker for an ERC-20 on Polygon PoS: every buy and sell in the last N minutes on the token's deepest WPOL/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. Costs $0.02 USDC on Base via x402.

Input Schema

NameRequiredDescriptionDefault
limitNoMax trades listed, 1 to 40, default 20
tokenYesToken contract address on Polygon PoS
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 carries the behavioral burden and does well: it discloses the $0.02 USDC x402 payment, the Polygon PoS scope, the Uniswap v3 WPOL/USDC pool source, and the returned fields such as USD size, side, wallet, volume, and net flow. It stops short of covering rate limits, error behavior, or empty-result handling.

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 a single dense but front-loaded sentence that leads with the core purpose and then adds scope, data fields, and cost. It contains no filler, though the long colon-and-semicolon structure is somewhat run-on.

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 data-retrieval tool with no output schema and no annotations, the description is largely complete: it explains the chain, data source, look-back window, returned metrics, and payment requirement. Minor gaps remain around edge cases and rate/error behavior, but an agent has enough to call it correctly.

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 parameter schema already defines token, limit, minUsd, and minutes with ranges and defaults. The description adds only loose alignment via phrases like 'last N minutes' and 'USD size', without meaningfully extending parameter semantics 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?

States a specific verb/resource combination: tracks whale and large trades for an ERC-20 on Polygon PoS. It narrows the scope to the token's deepest WPOL/USDC Uniswap v3 pools and enumerates the returned data, so it is clearly distinguishable from chain-specific siblings such as arbitrum_large_trades or eth_large_trades.

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 gives a clear usage context: it is for whale/large-trade tracking on Polygon PoS. It does not explicitly state when not to use it or name an alternative sibling, but the chain and dataset focus make the intended use obvious.

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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