ClearBounce Email Verification

Verify Email List (Bulk)

verify_bulk

Verify a list of email addresses (2 to 10,000) as one bulk job using the full ClearBounce bulk pipeline — per-domain caching and greylist retries give better accuracy than verifying one by one. Costs 1 credit per unique address; duplicates are removed for free. Returns a jobId immediately (the job runs in the background, roughly 1-10 minutes depending on size). Use check_bulk_status with the jobId to get progress and the final summary. Before starting a large list, confirm with the user that spending that many credits is intended.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`emails`	Yes	The email addresses to verify (2 to 10,000 items)

Output Schema

TableJSON Schema

Name	Required	Description
`note`	No
`jobId`	Yes	Use this with check_bulk_status
`uniqueEmails`	Yes	Addresses queued after duplicate removal — credits charged for these
`estimatedSeconds`	No	Rough time until the job completes
`duplicatesRemoved`	No

TDQS

A4.9/5.0

Behavior5/5

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

Beyond annotations, the description discloses that the job runs asynchronously in the background, takes roughly 1-10 minutes, costs 1 credit per unique address, deduplicates for free, and returns a jobId rather than immediate results. It also reveals a meaningful side effect (credit consumption) and the need for user confirmation, which annotations alone do not convey.

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?

The description is compact but information-dense. Purpose, accuracy benefit, cost model, async behavior, and follow-up action each appear in tight prose, and the most critical facts are front-loaded.

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 tool with one parameter and an output schema, the description covers everything needed to call it correctly: constraints, cost, async return, follow-up status polling, and user-confirmation guidance. It also distinguishes the tool from the sibling verify_email tool without needing further context.

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

Parameters4/5

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

The schema already documents the emails parameter and its 2-to-10,000 item range at 100% coverage, so the baseline is 3. The description adds valuable semantics beyond the schema: duplicates are removed for free and cost is calculated per unique address, so an agent understands the real meaning of the list contents.

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 opens with a specific verb and resource: 'Verify a list of email addresses (2 to 10,000) as one bulk job.' It also differentiates from single-address verification by highlighting the bulk pipeline's per-domain caching and greylist retries, so an agent can see why this tool exists apart from verify_email.

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?

The description explicitly explains when to choose bulk verification over one-by-one verification and names the follow-up tool, check_bulk_status, with the jobId. It also gives a clear behavioral instruction to confirm with the user before spending many credits, which is a strong usage guideline.

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

All ClearBounce Email Verification tools Inspect

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TDQS

A4.6/5.0

Disambiguation5/5

Each tool has a clearly distinct responsibility: real-time single verification, background bulk verification, bulk job status polling, credit balance lookup, and email discovery. The overlap between verify_email and verify_bulk is resolved by descriptions of real-time vs async batch processing.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using lowercase snake_case: verify_email, verify_bulk, check_bulk_status, check_credits, find_email. The naming convention is uniform and predictable.

Tool Count5/5

Five tools is well-scoped for an email verification service: single verification, bulk verification, status polling, credit tracking, and person email discovery. No redundant tools exist and each earns its place.

Completeness4/5

The set covers the core email verification lifecycle well, including single and bulk paths plus credit management. The only minor gap is that detailed bulk result files are accessible via the dashboard rather than the API, and there is no cancel/delete operation for bulk jobs.

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