check_typoSpot a likely typo in an email's domain (like gmial.com) and suggest the correct one, so you don't lose contacts to misspelled addresses. No credit used. Available on the Qualisend Pro plan.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | The email address to check for a typo. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable operational context not in the annotations: 'No credit used' and 'Available on the Qualisend Pro plan.' It also clarifies that the tool 'suggests' a correction, aligning with read-only behavior.
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, front-loaded with the core action, followed by an example, benefit, and operational notes. Every sentence adds value with no redundancy or filler.
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 with one parameter, and the description conveys the essential behavior. However, it does not specify the return format or what happens when no typo is found, and there is no output schema to compensate for this ambiguity.
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%, so the email parameter is already described as 'The email address to check for a typo.' The description adds a concrete example (gmial.com) that helps the agent understand what constitutes a typo, going slightly beyond the schema baseline.
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's verb and resource: 'Spot a likely typo in an email's domain' and 'suggest the correct one.' The example 'gmial.com' and benefit 'so you don't lose contacts to misspelled addresses' distinguish it from sibling verification tools such as verify_email or check_domain.
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 a clear use case ('so you don't lose contacts to misspelled addresses') that implies when to use the tool. However, it does not explicitly contrast with alternatives or state when not to use it, lacking exclusions or when-not 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.
Each tool targets a distinct function: single verification, synchronous batch, asynchronous bulk list, plus separate diagnostic checks (disposable, typo, domain, blacklist, header, SMTP code). The three verify tools are clearly differentiated by single vs. batch, sync vs. async, and size limits.
All tool names follow a consistent verb_noun pattern in snake_case: check_*, get_*, verify_*, generate_*, analyze_*, lookup_*. The batch variations (verify_emails, verify_list) are predictable extensions of verify_email.
12 tools is well within the ideal range for a focused email verification service. Each tool serves a clear purpose covering verification, diagnostics, DNS generation, and account management without unnecessary bulk.
The domain is well-covered: single/batch/large-list verification, common pre-check diagnostics, blacklist lookup, DNS record generation, and SMTP code explanations. Minor gaps include no history listing or batch job management beyond polling, but these are not core to the stated purpose.