email_auth_checkAudit a domain's email authentication setup: MX records, SPF record and DMARC policy, with a pass/warn/fail verdict per mechanism and an overall grade. Use it when diagnosing deliverability, hardening a domain against spoofing, or reviewing a vendor's email posture.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain to audit, e.g. github.com |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the output format (verdicts and overall grade) and what mechanisms are checked, but does not mention live DNS behavior, rate limits, permissions, or edge cases. It is adequate but not deeply transparent about operational details.
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: the first states the tool's function and outputs, the second lists concrete use cases. It is front-loaded and every sentence earns its place with no redundancy.
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?
The tool is simple (one parameter, no output schema). The description covers the purpose, the items inspected, the output verdict format, and intended scenarios. It lacks details on error cases or live lookup behavior, but for a straightforward audit tool, this is reasonably complete.
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% because the only parameter, 'domain', has a description with an example. The tool description adds minimal semantic value beyond the schema, as it only implies the domain is used for email auth checks. This matches the baseline for high schema coverage.
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 the tool audits a domain's email authentication setup, specifically MX, SPF, and DMARC, and provides pass/warn/fail verdicts with an overall grade. This is a specific verb+resource, and it distinguishes itself from sibling tools like dns_lookup and email_breach_check.
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 gives explicit use cases: diagnosing deliverability, hardening against spoofing, and reviewing vendor email posture. It does not state when not to use it or mention alternative tools, but the provided context is clear and actionable.
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.
Each tool targets a distinct resource and action. IP lookup, ASN, reverse DNS, blacklist, and VPN/proxy checks are clearly differentiated. Even the email tools focus on different mechanisms (auth vs breach).
All tools use consistent lower_snake_case, mostly following the <object>_<action> pattern. The few exceptions like my_ip and server_info still fit the overall style. There is no mixing of camelCase or inconsistent verb usage.
Fifteen tools is a well-scoped set for a comprehensive IP intelligence service. Each tool covers a unique capability without redundancy, and the count never feels bloated.
The surface covers the full lifecycle of IP investigation: lookups, reputation checks, batch processing, domain/DNS/email intelligence, and website security audits. Missing operations like SSL certificate checks are nice-to-have but not essential. The server_info tool also helps users discover capabilities.