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Pre-trade token check

pretrade_check
Read-only

Before trading a token on Base, Ethereum or Solana: its USD price and liquidity, plain warnings read from the chain, how big your planned trade is next to the pool (rough price impact), how much your wallet already holds, and recent web results about the token. Facts, not advice.

$0.01 USDC per call over x402. Failed calls cost nothing. Call without payment to get a quote.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNo"base" (default), "ethereum" or "solana".
tokenYesToken to check: ERC-20 contract or SPL mint ("SOL" works on Solana).
walletNoYour wallet address, to see how much of the token it holds.
paymentNoBase64 x402 payment payload. Omit it to receive a quote; sign that and call again.
amount_usdNoPlanned trade size in USD, to compare with pool depth.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses cost ($0.01 USDC per call over x402), that failed calls are free, and the two-step quote-then-sign flow when `payment` is omitted. It also sets a scope expectation with "Facts, not advice" — behavioral context the annotations cannot convey.

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 purpose and return contents are front-loaded in one dense sentence, followed by a compact second paragraph on pricing and the payment flow. Efficient overall, though the first sentence packs six comma-separated outputs into a single breath.

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?

With no output schema, the description correctly takes on the burden of describing what comes back (price, liquidity, warnings, impact, holdings, web results) plus cost and payment flow. The remaining gap is that it never positions itself against the many similarly named token/wallet balance siblings.

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 every parameter is already documented in the schema, giving a baseline of 3. The description restates parameter roles (trade size vs pool depth, wallet holdings, chain) at roughly the same level of detail as the schema, adding little beyond it.

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 states a specific pre-trade check and enumerates exactly what it returns: USD price, liquidity, on-chain warnings, rough price impact, wallet holdings, and web results. It is clear and concrete, but it never differentiates itself from near-named siblings like token_check, token_info, or token_price, leaving the agent to guess which one to call.

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?

"Before trading a token" gives a clear, actionable usage context, and the payment mechanics tell the agent the actual call sequence (quote first, then pay). However, it names no alternatives and gives no exclusions, despite several sibling tools that appear to overlap heavily in scope.

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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