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domain_intel__batch

Trust check for any domain in one call: DNS records, email auth (SPF/DMARC/DKIM), WHOIS registrar and age, live HTTP status, TLS certificate issuer/expiry and HSTS. Free /preflight returns the real records as a sample; paid /dns full report, /batch up to 10 domains. Price: $0.01 per call in USDC on Base (eip155:8453), paid with x402 in params._meta["x402/payment"]. HTTP: GET https://api.firstmention.uk/s/domain-intel/batch

Input Schema

NameRequiredDescriptionDefault
domainNoPublic domain name, e.g. example.com
domainsNoFor /batch: comma separated domains, max 10

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
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 well: it discloses a concrete price ($0.01/call in USDC on Base, eip155:8453), the x402 payment path (params._meta["x402/payment"]), the HTTP method and endpoint, and which endpoints are free vs paid. It stops short of failure behavior, rate limits, or result format, so it is strong but not exhaustive.

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?

The capability list is front-loaded in the first clause and the commercial terms follow in a compact second block with zero filler. It is dense but every clause (checks, free sample, price, payment field, endpoint) carries information.

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?

For a no-annotation, no-output-schema tool, the definition covers cost, payment, and report contents, which are the highest-risk unknowns. It is still incomplete on how the two parameters map to the three advertised endpoints and what an agent gets back (or what happens when payment is absent), which matters for a paid tool.

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 100%, so both parameters are already documented in the schema, and this is the baseline case. The description only reinforces the 'domains' parameter by stating '/batch up to 10 domains'; it adds no format, delimiting, or validation detail beyond what the schema provides, and says nothing about how 'domain' vs 'domains' interact.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb+resource framing ('Trust check for any domain') and enumerates exactly what is checked (DNS, SPF/DMARC/DKIM, WHOIS, HTTP status, TLS/HSTS). However, it bundles three endpoints (/preflight, /dns, /batch) into one definition, so it never makes clear whether this tool is the batch entry point or a general domain-intel tool, and it never distinguishes itself from the sibling domain_intel__dns.

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?

It hints at alternatives by mentioning the free /preflight sample and paid /dns full report versus /batch up to 10 domains, which implies a cost/volume choice. But it never states when an agent should pick this tool over domain_intel__dns, nor whether the 'domain' parameter routes to a single-domain mode — usage is left to inference.

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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