List MX records (exchange + priority, sorted) for a domain via free DNS-over-HTTPS to gauge mail deliverability. Accepts a bare domain or a full email address. Read-only; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| No | Email address (its domain is used if domain is omitted) | ||
| domain | No | Domain name (bare host) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavioral traits. It explicitly states 'Read-only; price 0.0 (free)' and mentions it uses 'free DNS-over-HTTPS', which are useful safety and cost signals. It does not cover edge cases like empty MX records or error behavior, but the read-only nature is well disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the primary action and outcome, and includes only high-value details (input flexibility, read-only, cost). No redundant phrasing; every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (DNS MX lookup), the description covers purpose, method, input format, safety, and cost. It also clarifies the output by naming 'exchange + priority, sorted'. No output schema exists, but the description sufficiently explains what will be returned. It is complete for an agent to select and invoke.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both 'email' and 'domain' having descriptions. The description adds a small clarification ('Accepts a bare domain or a full email address') and implies the email/domain relationship, but this largely restates what the schema already says. The baseline of 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action and resource: 'List MX records (exchange + priority, sorted) for a domain'. It also distinguishes from sibling tools by focusing solely on MX records for mail deliverability, unlike email_verify_check_spf or domain_intel_dns_lookup. The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it is used 'to gauge mail deliverability' and accepts either a bare domain or full email address. However, it does not explicitly mention when not to use this tool or name alternative tools, so it stops short of full exclusionary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly distinguished by domain prefixes (e.g., bid_watch, grant_watch) and specific action verbs. However, the high number of similarly structured watch tools could still cause confusion, though descriptions clarify exact purposes.
Every tool follows a consistent `domain_subdomain_action` pattern with underscores, e.g., `agent_audit_query`, `bid_watch_search`. Even long names like `commerce_catalog_agent_readiness_score` adhere to this structure.
With 147 tools, the server is far too broad, covering weather, carbon estimates, domain intel, and more—well beyond its stated 'Japan public-data ledgers' scope. This sheer volume overwhelms agents and dilutes focus.
The server offers many read-only tools for Japanese public data (bids, grants, licenses, etc.), but lacks create/update/delete operations for those domains. Additionally, numerous unrelated tools (e.g., carbon estimates, weather) feel tacked on, leaving gaps in core coverage.