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lordbasilaiassistant-sudo

base-security-scanner-mcp

check_honeypot

Detect honeypot tokens on Base mainnet by simulating buy/sell transactions through Uniswap V2 to identify trading restrictions and hidden taxes.

Instructions

Check if a token on Base mainnet is a honeypot by simulating buy and sell via Uniswap V2 router. Returns buy/sell ability and estimated taxes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
token_addressYesToken contract address on Base mainnet

Implementation Reference

  • The 'check_honeypot' tool implementation using the server.tool registration method and the simulateHoneypot helper function.
    server.tool(
      "check_honeypot",
      "Check if a token on Base mainnet is a honeypot by simulating buy and sell via Uniswap V2 router. Returns buy/sell ability and estimated taxes.",
      {
        token_address: z.string().describe("Token contract address on Base mainnet"),
      },
      async ({ token_address }) => {
        try {
          const metadata = await getTokenMetadata(token_address);
          const result = await simulateHoneypot(token_address);
    
          return ok({
            token: token_address,
            metadata: metadata ? serializeBigInts(metadata) as Record<string, unknown> : null,
            honeypotCheck: result,
          });
        } catch (err) {
          return fail(`check_honeypot failed: ${err instanceof Error ? err.message : String(err)}`);
        }
      }
    );
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the simulation method and return values, but does not cover important aspects like rate limits, authentication requirements, error conditions, or whether the simulation consumes resources (e.g., gas fees). The description adds value by explaining the simulation approach but misses key operational details.

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 a single, well-structured sentence that efficiently conveys purpose, method, and outcome without unnecessary words. It is front-loaded with the core action and avoids redundancy, making every part of the sentence earn its place.

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

Completeness3/5

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

Given the tool's complexity (simulating transactions), lack of annotations, and no output schema, the description is moderately complete. It covers the what and how but lacks details on behavioral traits (e.g., side effects, performance), error handling, and exact return structure. For a security analysis tool with simulation, more context would be beneficial to ensure safe and correct usage.

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 100%, so the schema already documents the single parameter ('token_address'). The description adds context by specifying it's for 'Base mainnet' and implies it's used for honeypot checking, but does not provide additional semantic details beyond what the schema states (e.g., format examples, validation rules). Baseline is 3 with high coverage, but the description slightly enhances understanding, warranting a 4.

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 specific action ('Check if a token... is a honeypot'), method ('by simulating buy and sell via Uniswap V2 router'), and outcome ('Returns buy/sell ability and estimated taxes'). It distinguishes itself from sibling tools like 'detect_rug_risk' or 'check_token_permissions' by focusing on honeypot detection via simulation rather than other security analyses.

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 description implies usage for honeypot detection on Base mainnet tokens, but does not explicitly state when to use this tool versus alternatives like 'detect_rug_risk' or 'audit_report'. It provides some context (e.g., 'on Base mainnet', 'via Uniswap V2 router') but lacks clear exclusions or comparative guidance with sibling tools.

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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