ZOOQ - LinkedIn Data for AI Agents

email_reverse

Read-onlyIdempotent

Resolve the person and company behind a BUSINESS email address. Public/role/disposable mailboxes are rejected (422, no charge) before any work runs. (Costs 10 Zooq credits.)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "email": "<email>"
    },
    "name": "email_reverse"
  }
}

Input Schema

Name	Required	Description	Default
`email`	Yes	A professional working mailbox. Public providers (gmail/outlook/…), role accounts (info@, support@), disposable and relay addresses are rejected with 422 (no credits charged).

Output Schema

Name	Required	Description
`email`	No	Example value was a string
`found`	No	Example value was a boolean
`person`	No
`confidence`	No	Example value was a string
`current_company`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 1, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds meaningful context beyond that: it discloses the 422 rejection behavior for invalid address types (with no charge), and states the cost (10 credits). This gives the agent important operational knowledge about failure modes and pricing, which annotations 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.

Conciseness5/5

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

The description is compact at three sentences, with the primary purpose front-loaded in the first sentence. It efficiently conveys the rejection behavior and cost without redundancy. Every sentence earns its place.

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 single-parameter tool with a well-documented schema, clear annotations, and an output schema present, the description covers what agents need: purpose, input constraints, failure response, and cost. There are no significant missing details that would impede correct invocation.

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?

The sole parameter 'email' is fully described in the schema (100% coverage), and the description's mention of rejection types mirrors that schema text. The description adds no new parameter-specific meaning beyond what the schema already states. Thus the baseline of 3 is appropriate; no extra value provided.

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 'Resolve the person and company behind a BUSINESS email address', a specific verb and resource that clearly states the tool's function. It also distinguishes itself from siblings like email_find and email_verify by emphasizing reverse-lookup (resolving owner from an address) and by restricting to business emails, explicitly excluding public/role/disposable addresses.

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

Usage Guidelines4/5

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

The description implies when to use the tool: it is for business emails only, and public/role/disposable addresses are rejected. While it doesn't explicitly name alternative tools, the context of siblings (email_find, email_verify) makes the intended usage clear. A note on using this when you have a professional email and need the associated person/company would be a minor improvement.

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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