Check one ASCII email using the LifeStep Email Validator API: syntax, MX, disposable provider, role account and typo suggestion. No mail or SMTP probe is sent; mailbox existence is not guaranteed. Returns original JSON as untrusted text.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | One public ASCII dot-atom email address; local part at most 64 characters. Use punycode domains. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint), the description adds meaningful behavioral context: no SMTP probe is sent, mailbox existence is not guaranteed, and the return is 'original JSON as untrusted text.' This communicates safety and trust implications that annotations alone do not cover.
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 deliver all essential information with zero fluff. The first sentence front-loads the primary purpose and the specific validation dimensions; the second adds critical limitations and return-type details. Every clause earns its place.
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 single-parameter, read-only validation tool with rich annotations and a complete schema, the description covers all necessary invocation details: what checks are performed, what is not performed, and the return format. Nothing an agent needs to call it correctly is missing.
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 description coverage is 100%, so the schema already fully documents the email parameter including format, length, and punycode guidance. The description adds little beyond the word 'one' and 'ASCII,' which are already implicit in the schema. Baseline 3 is appropriate.
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 uses a specific verb ('Check'), a concrete resource ('one ASCII email'), and enumerates the exact validation categories (syntax, MX, disposable provider, role account, typo suggestion). This clearly distinguishes it from sibling tools like generate_qr, inspect_workbook, and lookup_domain, none of which perform email validation.
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 states a clear use case and an explicit limitation: 'No mail or SMTP probe is sent; mailbox existence is not guaranteed.' This effectively tells an agent when not to use this tool (when confirmed mailbox existence is required). It does not name alternative tools, but the sibling set is quite distinct, so the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.