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47620 Multichain On-chain Data API

risk_check

BEFORE paying an address, get a 0-100 risk score with reasons and a proceed/review verdict, built from re-verifiable on-chain facts. chain -> /x/solana/risk/:address | /x/base-fac/risk/:address | /x/polygon-fac/risk/:address. Pay-per-call ($0.02 USDC).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainYesChain to query
addressYesAddress to check before paying (0x... EVM or base58 Solana)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • changedInput schema / properties / address / description
      Previous value: -"Solana address to check before paying"New value: +"Address to check before paying (0x... EVM or base58 Solana)"
    • addedInput schema / properties / chain
      Added value: +{
      +  "description": "Chain to query",
      +  "enum": [
      +    "solana",
      +    "base",
      +    "polygon"
      +  ],
      +  "type": "string"
      +}
    • changedInput schema / required
      Previous value: -[
      -  "address"
      -]New value: +[
      +  "chain",
      +  "address"
      +]
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It discloses the pay-per-call cost ($0.02 USDC), the re-verifiable on-chain fact basis, and the output verdict, but it never explicitly states read-only status, rate limits, or auth beyond payment.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the primary use case and output, then compactly lists chain endpoints and cost. Every line carries information; the endpoint mapping is dense but purposeful, so it is efficiently structured.

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 no-annotation, no-output-schema tool, the description covers the essential context: when to use, what it returns, which chains, and the cost. It leaves minor gaps (read-only status, error behavior), but an agent has enough to invoke 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 coverage is 100%, so the schema already documents both parameters. The description adds a chain-to-endpoint mapping, but doesn't add syntax or constraints beyond the schema's enum and address description, so baseline 3 is appropriate.

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 verb ('get') and resource ('risk score') with output detail ('0-100 risk score with reasons and a proceed/review verdict'). It does not explicitly distinguish from siblings like trust_check or should_pay, so it is clear but lacks sibling differentiation.

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?

It gives a clear usage context ('BEFORE paying an address'), which is when to use it. It offers no when-not guidance or named alternatives among siblings, so it falls short of a 5.

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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