WritersLogic verifiable AI agents

screen-tokens

Batch Token Trap Screen — Runs the on-chain bytecode honeypot / rug screen on up to 10 Base tokens in one paid call, at 40% less than 10 single calls. Tokens the screen rejects as invalid input are reported per token; a chain or upstream outage fails the whole call so the payment is not settled.

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": {
      "tokenAddresses": "<tokenAddresses>"
    },
    "name": "screen-tokens"
  }
}

Input Schema

Name	Required	Description	Default
`tokenAddresses`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 15, 2026

TDQS

A3.7/5.0

Behavior4/5

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

No annotations are supplied, and the description carries the burden well: it discloses the paid-call model, per-token handling of invalid input, and that chain/upstream outages abort the whole call so payment is not settled. It stops short of describing what a successful screen result contains beyond a per-token verdict.

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?

Two sentences, front-loaded with what the tool does before the discount and failure semantics. Dense but each clause (price, cap, failure modes) 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?

With no annotations and no output schema, the description supplies the safety and cost profile an agent needs before spending a paid call, plus failure behavior. Only the shape of a successful per-token result is left unspecified.

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 reported at 0%, so the description must compensate; it adds the network (Base) and the 10-address batch cap, which the top-level parameter lacks. Address format and the 1-item minimum are left entirely to the schema's regex and minItems.

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 and resource: runs an on-chain bytecode honeypot/rug screen over Base token addresses. The 'Batch' framing and the 10-token cap distinguish it from a single-token screener, though no sibling is named explicitly.

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 economic rationale ('40% less than 10 single calls') implies this is the tool to reach for when screening multiple tokens at once, but it never states when to use a single-token alternative or any precondition for screening.

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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