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Verify a batch of email addresses

verify_batch
Read-only

Synchronously verify a list of email addresses (best for up to a few hundred). Returns a per-address verdict for each email. For very large lists use the bulk async endpoint instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailsYesArray of email addresses to verify.
exclude_role_accountsNoFlag/exclude role accounts (info@, sales@, ...). Default false.
exclude_public_domainsNoFlag/exclude public domains (gmail.com, ...). Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so safety is covered. The description adds genuinely new context: synchronous execution model, practical batch-size ceiling, and the shape of the result (per-address verdict). It omits rate limits, credit cost, and partial-failure behavior, so it falls short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with what the tool does and why the sync path exists. Every sentence earns its place: purpose, return shape, and the routing condition to the alternative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a three-parameter read tool with full schema coverage and no output schema, the description supplies the sync/async distinction and the return value shape, which is what an agent needs to call it correctly. Remaining gaps (cost, rate limits, error semantics) are minor but nonzero.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and all three parameters (emails, exclude_role_accounts, exclude_public_domains) carry their own descriptions with defaults. The description adds no parameter-level detail beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (synchronously verify a list of email addresses) and scopes it ('best for up to a few hundred'), which cleanly separates it from verify_email (single) and submit_bulk (async large lists). An agent can route correctly without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly gives the when ('best for up to a few hundred') and the when-not with a named alternative path ('For very large lists use the bulk async endpoint instead'). Both the selection condition and the escape hatch are stated, not inferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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