Check an email address for disposable, spam, gibberish, or fraud risk before using it for signups, outreach, or account verification.
Check if an email is disposable, spam, gibberish or fraud risk.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | Email address to check. |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full behavioral burden, and it discloses almost nothing beyond the risk categories. It doesn't say whether this hits an external service, what the returned verdict looks like (boolean, category list, score), whether results are cached, or whether there are latency/rate constraints. For an unannotated tool with no output schema, this is a significant disclosure 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?
One sentence, front-loaded with the verb and resource, with the risk categories listed immediately after. Zero filler or 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, but with no annotations and no output schema, the description should explain what a caller gets back — a per-category result, an overall verdict, or a confidence score. That return-shape information is entirely absent, leaving an agent unable to plan how to consume the result.
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?
There is a single required parameter and the schema already documents it at 100% coverage ('Email address to check.'), so the schema does the work here. The description adds no format constraints, normalization rules, or edge-case notes (e.g., case sensitivity, unicode) beyond what the schema provides.
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?
Names a specific verb ('check') and resource ('an email') and enumerates the exact risk categories evaluated: disposable, spam, gibberish, fraud. An agent can immediately tell what the tool does. It doesn't explicitly differentiate from the sibling tools, but they (search tasks, account status) are obviously unrelated domains, so misselection risk is low.
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?
Usage is implied by the description — you call it when you need to validate the risk profile of an email address. However, there is no explicit when-to-use or when-not-to-use framing, no mention of prerequisites, and no named alternative for related checks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.