Sausage Trust

Domain registration & DNS card

domain_intel

RDAP registration card for a domain (creation/expiry dates, registrar, statuses, nameservers, DNSSEC) plus derived risk flags like domain age. view='dns' returns a live multi-record DNS summary (A/AAAA/CNAME/MX/NS/TXT/SOA/CAA + SPF/DMARC); view='live' re-reads the registry at the moment you ask. Paid: call without x_payment to receive this call's exact terms (amount, asset, network), sign them, then call again with x_payment. The free pricing tool lists every price at once.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`view`	No	Which read to perform.	registration
`domain`	Yes	Registrable domain name.
`x_payment`	No	Optional signed x402 payment payload (base64, what the X-PAYMENT header carries). Omit to receive the exact payment terms; sign them (e.g. @x402/fetch) and call again with this argument to settle and get the data.

TDQS

A4.7/5.0

Behavior5/5

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

With no annotations, the description fully discloses behavior: the default registration view, the 'dns' view returning live multi-record DNS summaries, the 'live' view re-reading the registry, and the paid x_payment flow (call without payment to get terms, sign, then call again). This is transparent about payment requirements and operational semantics.

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?

Three dense sentences, front-loaded with the core purpose, followed by view specifics and payment instructions. Every clause adds value, with no repetition or filler. The DNS record list is long but necessary for expected output.

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?

For a 3-parameter tool with no output schema and no annotations, the description covers the purpose, all three views, the contents of each view, and the payment workflow. It provides enough return-value context (registration fields, DNS records) and behavioral details to guide an agent without requiring additional documentation.

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 coverage is 100%, so baseline is 3. The description adds semantic meaning beyond schema: it enumerates the DNS record types returned in the 'dns' view (A/AAAA/CNAME/MX/NS/TXT/SOA/CAA + SPF/DMARC), clarifies that 'live' re-reads the registry, and elaborates the x_payment handshake. This enriches parameter understanding.

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 identifies a specific action: returning an RDAP registration card for a domain, and enumerates exact data fields (creation/expiry dates, registrar, statuses, nameservers, DNSSEC) plus derived risk flags. It also distinguishes DNS and live views. This is clearly distinct from sibling tools focused on other entity types, such as email_check or sanctions_entity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states the tool is for domain registration and DNS intel, and even points to the free 'pricing' tool as an alternative for cost listing. However, it does not explicitly exclude overlapping sibling tools like url_screen or find_data, leaving some ambiguity around when to choose this over those.

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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TDQS

A4.2/5.0

Disambiguation5/5

Each tool targets a distinct resource type (crypto address, domain, email, IBAN, phone, URL, vessel, entity name) or a distinct purpose (pricing, data discovery, data request). Overlapping sanctions tools are clearly differentiated by target: address_screen for addresses, sanctions_screen for names, vessel_screen for vessels, and sanctions_entity for detailed records after screening.

Naming Consistency3/5

Most data-check tools follow a consistent object_verb pattern (e.g., address_screen, email_check, phone_check). However, find_data and request_data invert the order, domain_intel uses a noun instead of a verb, and pricing stands alone as a gerund, creating mixed conventions.

Tool Count5/5

12 tools is well within the ideal range for a data-screening server. Each tool covers a distinct verification task, and the additional meta tools (pricing, find_data, request_data) are useful entry points without bloating the core purpose.

Completeness4/5

The server covers a comprehensive set of screening and validation tasks across sanctions, domain, email, phone, IBAN, and URL. It includes a discovery tool (find_data) and a suggestion tool (request_data) to fill gaps, though an IP checker or company registry lookup could be considered minor omissions.

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