Check whether a domain is a known disposable / throwaway email provider against a bundled list. Accepts a bare domain or a full email address. Pure; 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?
No annotations are provided, so the description carries the full burden. It discloses that the check is against a 'bundled list' (suggesting a local/offline lookup) and states 'Pure; price 0.0 (free)' indicating no side effects and no cost. However, it does not describe the return value or behavior for unknown domains, which is a notable gap.
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 short sentences, front-loaded with the core purpose, then mentions input flexibility and cost. Every sentence adds value, with no redundant phrases.
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 simple two-parameter tool with no output schema and no annotations, the description covers the core action, input flexibility, and cost. The main omission is the return format, but given the simplicity and the clarity of 'check whether', a score of 4 is appropriate.
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%, and the schema already explains that 'email' uses its domain if 'domain' is omitted. The description essentially restates this input flexibility without adding new meaning beyond what the schema provides. Baseline 3 applies.
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 ('Check whether a domain is a known disposable / throwaway email provider') and identifies the resource ('bundled list'). It is distinct from sibling tools like email_verify_check_mx or email_verify_verify_syntax, which target different verification aspects.
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 implies usage when detecting disposable email providers, and clarifies input flexibility ('Accepts a bare domain or a full email address'). However, it does not explicitly mention when not to use this tool or suggest alternatives among the email_verify_* 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.
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.