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token.risk

Read-onlyIdempotent

Due diligence before buying any token (Base by default; also ethereum, arbitrum, optimism, polygon, solana). EVM: simulated sell and buy (honeypot check), owner and upgradeable proxy, mint, blacklist, pause and fee functions, liquidity, LP burn, observed buy tax, last-hour flow. Solana mints: mint and freeze authority, Token-2022 transfer fee, permanent delegate, transfer hook, pause and top-wallet concentration. Verdict LOW_RISK, CAUTION or HIGH_RISK. Use before buying a token; for the price you would get on chain use token.swap_quote.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNoChain of the token or pool: base (default), ethereum, arbitrum, optimism or polygon (solana where listed). Not the payment networkbase
addressYes0x-prefixed ERC-20 contract, or a base58 Solana mint

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / chain / description
      Previous value: -"Chain of the token or pool: base (default), ethereum, arbitrum, optimism or polygon (solana where listed)"New value: +"Chain of the token or pool: base (default), ethereum, arbitrum, optimism or polygon (solana where listed). Not the payment network"
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, openWorld), and the description still adds substantial context: the specific checks performed (honeypot simulation, owner/proxy, mint, blacklist, tax, LP burn, flow; Solana mint/freeze authority, Token-2022 hooks, concentration) and the categorical verdict it returns.

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?

Front-loaded with purpose and usage, followed by a dense but relevant enumeration of checks and a pointer to the sibling tool. The mid-sentence check list is long, but every item carries selection value.

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

Completeness5/5

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

With no output schema, the description compensates by explaining the return verdict categories and the full scope of analysis per chain, which is everything an agent needs to decide whether to call it.

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 both parameters are already documented. The description restates the supported chains and the Base default plus the 'not the payment network' clarification, which is useful framing but adds little syntax or format meaning 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?

Opens with a specific verb+resource ('Due diligence before buying any token') and enumerates exactly what is inspected for EVM versus Solana mints, including the LOW_RISK/CAUTION/HIGH_RISK verdict. It is clearly distinguishable from siblings like token.swap_quote and token.new_launches.

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

Usage Guidelines5/5

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

Explicitly states the trigger ('Use before buying a token') and names the alternative tool with its selecting condition ('for the price you would get on chain use token.swap_quote'). No inference required.

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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