Rug Munch Intelligence

check_token_risk

Analyze token security risks before transactions by evaluating rug pull potential, honeypot detection, deployer history, and holder concentration to provide risk scores and safety recommendations.

Instructions

CRITICAL: Check a token's rug pull risk score BEFORE any transaction. Returns 0-100 risk score, honeypot detection, deployer history, freeze authority check, holder concentration, and SAFE/CAUTION/AVOID recommendation. Cost: $0.04 per check. The cheapest insurance in crypto.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "token_address": "<token_address>"
    },
    "name": "check_token_risk"
  }
}

Input Schema

Name	Required	Description	Default
`token_address`	Yes	Token mint address (Solana) or contract address (EVM)
`chain`	No	Blockchain: solana, ethereum, base, arbitrum, polygon, optimism, avalanche	solana

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Mar 13, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and effectively discloses key behavioral traits: it's a read-only risk assessment tool (implied by 'check'), includes cost information, and details the comprehensive output (risk score, honeypot detection, etc.), though it lacks specifics on rate limits or error handling.

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 critical information ('CRITICAL: Check...'), uses efficient sentences that each add value (purpose, output details, cost), and avoids redundancy, making it highly concise and well-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?

Given the complexity of risk assessment, no annotations, and no output schema, the description is mostly complete: it covers purpose, usage timing, output details, and cost. However, it lacks information on response format or error cases, leaving minor gaps for a tool with rich functionality.

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 baseline is 3. The description adds no additional parameter semantics beyond what the schema provides (e.g., it doesn't explain token_address formats or chain implications), but it doesn't need to compensate as schema coverage is high.

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?

The description clearly states the tool's purpose with specific verbs ('check', 'returns') and resources ('token's rug pull risk score'), and distinguishes it from siblings by emphasizing it's for individual token risk assessment before transactions, unlike batch or premium checks.

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?

It explicitly states when to use this tool ('BEFORE any transaction') and provides context on cost ('$0.04 per check'), helping users decide between this and alternatives like check_batch_risk or check_token_risk_premium based on urgency and budget.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.