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Davison-Francis

@deliveriq/mcp

Submit Batch Verification

deliveriq_batch_verify

Submit a batch of 1 to 10,000 email addresses for asynchronous verification. Returns a job ID for tracking progress. Optionally skip SMTP verification or set a webhook for completion events.

Instructions

Submit a batch of email addresses for asynchronous verification. Returns a job ID for tracking.

Use deliveriq_batch_status to poll progress, and deliveriq_batch_download to get results when complete.

Args:

  • emails (string[]): Array of 1-10,000 email addresses

  • skip_smtp (boolean): Skip SMTP verification (default: false)

  • callback_url (string, optional): Webhook URL for batch.completed/batch.failed events

Returns: Job ID, status, estimated completion time, and status polling URL.

Examples:

  • "Verify these 3 emails" -> { emails: ["a@ex.com", "b@ex.com", "c@ex.com"] }

  • "Batch verify with webhook" -> { emails: [...], callback_url: "https://my-app.com/webhook" }

Credit cost: 1 credit per email

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailsYesArray of email addresses to verify (1-10,000)
skip_smtpNoSkip SMTP verification for all emails
callback_urlNoWebhook URL to receive batch.completed or batch.failed event
Behavior5/5

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

Discloses async behavior, job ID return, polling URL, and webhook events (batch.completed/batch.failed). Annotations indicate non-readonly, non-destructive, non-idempotent, open world; description aligns and adds valuable context beyond annotations.

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?

Well-structured with clear sections (purpose, usage, args, returns, examples, cost). Each sentence is informative without redundancy. Concise yet comprehensive.

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

Completeness5/5

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

For a 3-param tool with no output schema, description covers return fields (Job ID, status, etc.), credit cost, async flow, and webhook integration. Contextually complete for an agent to select and invoke correctly.

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

Parameters5/5

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

With 100% schema coverage, baseline is 3, but description adds: email array range (1-10,000), skip_smtp default false, callback_url webhook events, and illustrative examples. This adds significant meaning beyond the schema.

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?

The description clearly states the action (submit), resource (batch of email addresses), and purpose (asynchronous verification) with the verb 'Submit'. It distinguishes from sibling tools by mentioning tracking via job ID and referencing polling and download tools.

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 instructs to use deliveriq_batch_status for polling and deliveriq_batch_download for results, providing clear when-to-use guidance. Also mentions credit cost per email for context.

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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