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Dragons Eye Ransomware Claims

bulk_vendor_check

Read-onlyIdempotent

Check up to 100 vendors (domains or company names) for ransomware leak-site claims in one call: per vendor, matching claims (group, dates, sources), claim count and groups. Raw claims only; use vendor_risk_report for risk levels, a summary and actions. Every result is an unverified claim from a criminal leak site, not a confirmed breach; found=false is not proof of absence. Fails (not charged) if the source is down for more than 25% of vendors. Read-only. Costs $0.50 USDC per call via x402 (payment goes in _meta["x402/payment"]); invalid input or an upstream failure returns an error and is not charged.

Input Schema

NameRequiredDescriptionDefault
vendorsYesVendor domains or company names, 1-100, e.g. ["acme.com", "Example Corp"]

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only cover the safety profile (readOnly, idempotent, openWorld, non-destructive), and the description goes well beyond them: results are unverified criminal leak-site claims rather than confirmed breaches, found=false is not proof of absence, and it discloses the failure threshold, the $0.50 x402 charge, where payment goes (_meta["x402/payment"]), and that errors/invalid input are not charged. This is exactly the extra behavioral context annotations cannot express.

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?

Front-loaded with the core action and scope in the first clause, then each subsequent clause adds distinct, non-redundant information (output fields, alternative tool, data caveat, failure policy, cost/payment). No filler sentences.

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

Completeness5/5

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

Despite having no output schema, the description names the returned fields, clarifies the semantics of a negative result, and covers pricing, payment transport, and error billing. For a one-parameter batch lookup tool, an agent has everything needed to call it correctly and interpret the result.

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% and the single parameter already documents the 1-100 range, 200-char limit and examples, so the schema carries the burden. The description restates 'up to 100 vendors (domains or company names)' without adding syntax or format meaning beyond the schema, so the baseline 3 applies.

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?

States a specific verb (Check), resource (vendors: domains or company names), scope (up to 100, ransomware leak-site claims, one call), and enumerates the per-vendor return shape (group, dates, sources, claim count, groups). It also names the sibling it is not (vendor_risk_report), so an agent can distinguish it without opening either schema.

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?

Explicitly routes the agent: raw claims here, but 'use vendor_risk_report for risk levels, a summary and actions.' It also gives the pathological condition (fails if the source is down for more than 25% of vendors) and the cost model, so the agent knows both when to pick it and what to expect when it degrades.

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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