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Get Registration Requirements

get_registration_requirements
Read-onlyIdempotent

Retrieve a TLD's registration requirements as JSON Schema to confirm API registerability and build valid registration payloads before calling register_domain.

Instructions

Get a TLD's registration requirements as JSON Schema. Returns whether the TLD is registerable via the API (apiRegisterable), the register_domain request body as a JSON Schema (with the fixed term, cost, agreeToTerms), WHOIS-privacy / validated-address / registrant-only flags, and — for TLDs with registry eligibility rules (e.g. .us nexus, .ca legal type) — a second schema (registryRequirements) listing those fields with allowed values and labels. Call this BEFORE register_domain to confirm a TLD can be registered and to build a valid payload, instead of discovering requirements from a failed registration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tldYesTLD without a leading dot, e.g. `com`, `us`, `ca`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.39.4

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/openWorldHint=false, so the safety profile is covered. The description adds real value by disclosing what is returned (registerability flag, request-body schema, registry eligibility fields) — significant given there is no output schema. It stops short of error/auth behavior, so not a 5.

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?

Front-loaded with the core action, then the return shape, then the usage directive. It is a dense single paragraph but each clause carries distinct information; only the long parenthetical about .us/.ca could be trimmed.

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?

With no output schema, the description must explain what comes back, and it does so thoroughly — including the two-schema structure and the registry-requirements edge case. An agent has everything needed to call it correctly before register_domain.

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 `tld` parameter is fully documented in the schema (including the no-leading-dot format), so the baseline of 3 applies. The description only refers to 'a TLD' generically and adds no syntax beyond the schema.

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 (get) and resource (TLD registration requirements) and enumerates the concrete payload contents (apiRegisterable, register_domain body schema, privacy/address/registrant flags, registryRequirements). This clearly separates it from siblings like check_domain, preflight_domain, and register_domain.

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 instructs 'Call this BEFORE register_domain to confirm a TLD can be registered and to build a valid payload, instead of discovering requirements from a failed registration.' That is a named alternative plus the condition and the anti-pattern to avoid — no inference required.

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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