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Crypto Market

by io.github.gojisatoshi888
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rug_risk

Rug-pull / honeypot score from 0 to 100 using GoPlus, DexScreener, and RugCheck on Solana. chain is ethereum, bsc, base, or solana (eth, bnb, and sol also work). Trusted tokens still list issuer-style flags but those flags do not add points. include_summary adds an InferHub paragraph. Paid tool: $0.02 USDC per call via x402 on eip155:8453. The first few calls each UTC day are free; after that an unpaid call returns PaymentRequired and does not charge.

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>",
      "chain": "<chain>"
    },
    "name": "rug_risk"
  }
}

Input Schema

NameRequiredDescriptionDefault
chainYes
token_addressYes
include_summaryNo

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 full burden and does substantial work: cost ($0.02 USDC via x402 on eip155:8453), a free daily quota, and the exact failure mode (PaymentRequired with no charge). It also discloses a non-obvious scoring rule — that trusted tokens still list issuer-style flags but those flags earn no points. It stops short of describing pagination/latency or whether scoring is deterministic across providers.

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?

Purpose, chain vocabulary, and cost terms are packed into a short, front-loaded block with no filler. The phrasing is dense and slightly run-on (three unrelated facts in adjacent clauses), but every sentence contributes information.

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 3-parameter tool with no annotations and no output schema, the definition covers cost, failure behavior, chain vocabulary, and output shape (0-100 score plus optional summary). The remaining gap is what the response body actually contains (individual flags, provider disagreements), which the absence of an output schema leaves undocumented.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it defines `chain` well (accepted values plus the eth/bnb/sol aliases) and explains what `include_summary` adds (an InferHub paragraph). `token_address` is left entirely unexplained, which is the one gap given a zero-coverage 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 and the output scale: a rug-pull/honeypot score 0-100, plus the named data sources (GoPlus, DexScreener, RugCheck). It is unambiguous against siblings like get_price or fear_greed, which return market data rather than token-safety assessments.

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

Usage Guidelines3/5

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

The context for calling is implied by the purpose (screening a token before exposure), and the payment mechanics tell the agent what happens on repeated calls. However, there is no explicit when-to-use/when-not guidance and no routing to or away from any sibling tool.

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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