check_domain_healthCheck the DNS and deliverability health of an email domain: MX records, SPF, DMARC, and an overall health score. Useful for diagnosing why a domain bounces or for validating a sending domain.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain to check, e.g. example.com |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It explicitly lists the checks performed (MX, SPF, DMARC, overall score) and implies a read-only operation. It does not disclose potential limitations or API-specific behaviors like rate limits.
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?
Two sentences contain all essential information with no fluff. The key details are front-loaded.
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?
For a tool with one parameter, no output schema, and no annotations, the description provides sufficient context: what is checked, why it's useful, and the single input. It is complete for its complexity.
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?
The single parameter 'domain' is fully described in the schema (100% coverage). The description adds no extra meaning beyond what the schema already provides, which is acceptable for a simple parameter.
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?
Description clearly states that the tool checks email domain health including MX, SPF, DMARC, and an overall health score. It distinctly serves a different purpose from sibling tools like verify_email which check individual addresses.
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 explicit use cases: 'diagnosing why a domain bounces or for validating a sending domain.' However, it does not mention when not to use this tool or alternatives among siblings.
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 has a clearly distinct purpose. Overlaps like verify_batch vs submit_bulk are explicitly differentiated by synchronous vs asynchronous behavior. Extraction, cleaning, verification, and management tools are well-separated.
All tool names follow a consistent verb_noun pattern (e.g., register_account, verify_email, get_job_status). There is no mixing of conventions or vague verbs.
15 tools cover the domain of email verification and account management without redundancy. Each tool fills a specific role—single verification, batch sync, bulk async, job polling, results retrieval, list cleaning, extraction, domain health, credit purchasing, and account management.
The tool set provides complete lifecycle coverage: account registration, usage tracking, credit purchase, email verification (single, batch, bulk with async), job management, list cleaning, email extraction, and domain health checks. No obvious gaps for the intended functionality.