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honeypot_check

Read-only

RugRadar honeypot check: can I sell this token? Simulated buy/sell and tax on EVM chains, live Jupiter sell quote plus freeze/mint authority and token-2022 transfer controls on Solana; 0-100 risk score. $0.01 per check: 45+ data points per token, including 16 signals RugCheck's free report doesn't show (dev-sold %, sniper and launch-bundle share, a live can-you-sell quote, the creator's past launches, volume vs market cap, bot-trading score), across 5 chains.

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": "<token>"
    },
    "name": "honeypot_check"
  }
}

Input Schema

NameRequiredDescriptionDefault
chainNodefault solana; 0x addresses default to base
tokenYesSolana mint or EVM 0x token contract
api_keyNooptional RugRadar credit key (or send header X-RugRadar-Key)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

With readOnlyHint and openWorldHint already declared, the description usefully adds cost ($0.01 per check), breadth (45+ data points, 5 chains), and the nature of the analysis (simulated trades, live Jupiter quote, authority checks). It does not describe latency, rate limits, or failure behavior, but the pricing and coverage disclosures are meaningful context beyond the annotations.

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 is front-loaded in the first clause and the rest is a single dense paragraph with no true filler sentences. The parenthetical list of six named signals leans toward marketing copy, but it still conveys what the check returns.

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?

No output schema exists, so the description must convey the return shape — it does via the 0-100 risk score, 45+ data points, and enumerated signal categories. Combined with the cost and chain coverage, an agent has enough to call it correctly, though a clearer contrast with the two sibling tools would close the last gap.

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 chain/token/api_key semantics are already documented, including the chain default and the 0x-address rule. The description only corroborates scope ('across 5 chains') without adding format or syntax detail, so the baseline 3 applies.

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?

States a specific verb+resource — 'honeypot check: can I sell this token?' — and spells out the mechanics (simulated buy/sell and tax on EVM, live Jupiter sell quote plus freeze/mint authority and token-2022 controls on Solana). It partially distinguishes itself from the rug_check sibling by citing '16 signals RugCheck's free report doesn't show', but never addresses token_safety, so differentiation is implicit rather than crisp.

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?

Usage is only implied: the '16 signals RugCheck's free report doesn't show' framing suggests this is the deeper/paid option, but there is no explicit statement of when to pick honeypot_check over rug_check or token_safety, and no exclusions. The reader must infer the routing logic.

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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